what is inductive hypothesis in research

Inductive Approach (Inductive Reasoning)

Inductive approach, also known in inductive reasoning, starts with the observations and theories are proposed towards the end of the research process as a result of observations [1] .  Inductive research “involves the search for pattern from observation and the development of explanations – theories – for those patterns through series of hypotheses” [2] . No theories or hypotheses would apply in inductive studies at the beginning of the research and the researcher is free in terms of altering the direction for the study after the research process had commenced.

It is important to stress that inductive approach does not imply disregarding theories when formulating research questions and objectives. This approach aims to generate meanings from the data set collected in order to identify patterns and relationships to build a theory; however, inductive approach does not prevent the researcher from using existing theory to formulate the research question to be explored. [3] Inductive reasoning is based on learning from experience. Patterns, resemblances and regularities in experience (premises) are observed in order to reach conclusions (or to generate theory).

Application of Inductive Approach (Inductive Reasoning) in Business Research

Inductive reasoning begins with detailed observations of the world, which moves towards more abstract generalisations and ideas [4] . When following an inductive approach, beginning with a topic, a researcher tends to develop empirical generalisations and identify preliminary relationships as he progresses through his research. No hypotheses can be found at the initial stages of the research and the researcher is not sure about the type and nature of the research findings until the study is completed.

As it is illustrated in figure below, “inductive reasoning is often referred to as a “bottom-up” approach to knowing, in which the researcher uses observations to build an abstraction or to describe a picture of the phenomenon that is being studied” [5]

Here is an example:

My nephew borrowed $100 last June but he did not pay back until September as he had promised (PREMISE). Then he assured me that he will pay back until Christmas but he didn’t (PREMISE). He also failed in to keep his promise to pay back in March (PREMISE). I reckon I have to face the facts. My nephew is never going to pay me back (CONCLUSION).

Generally, the application of inductive approach is associated with qualitative methods of data collection and data analysis, whereas deductive approach is perceived to be related to quantitative methods . The following table illustrates such a classification from a broad perspective:

However, the statement above is not absolute, and in some instances inductive approach can be adopted to conduct a quantitative research as well. The following table illustrates patterns of data analysis according to type of research and research approach .

When writing a dissertation in business studies it is compulsory to specify the approach of are adopting. It is good to include a table comparing inductive and deductive approaches similar to one below [6] and discuss the impacts of your choice of inductive approach on selection of primary data collection methods and research process.

My e-book,  The Ultimate Guide to Writing a Dissertation in Business Studies: a step by step assistance  contains discussions of theory and application of research approaches. The e-book also explains all stages of the  research process  starting from the  selection of the research area  to writing personal reflection. Important elements of dissertations such as  research philosophy ,  research design ,  methods of data collection ,  data analysis  and  sampling  are explained in this e-book in simple words.

John Dudovskiy

[1] Goddard, W. & Melville, S. (2004) “Research Methodology: An Introduction” 2nd edition, Blackwell Publishing

[2] Bernard, H.R. (2011) “Research Methods in Anthropology” 5 th edition, AltaMira Press, p.7

[3] Saunders, M., Lewis, P. & Thornhill, A. (2012) “Research Methods for Business Students” 6 th  edition, Pearson Education Limited

[4] Neuman, W.L. (2003) “Social Research Methods: Qualitative and Quantitative Approaches” Allyn and Bacon

[5] Lodico, M.G., Spaulding, D.T &Voegtle, K.H. (2010) “Methods in Educational Research: From Theory to Practice” John Wiley & Sons, p.10

[6] Source: Alexandiris, K.T. (2006) “Exploring Complex Dynamics in Multi Agent-Based Intelligent Systems” Pro Quest

Want to create or adapt books like this? Learn more about how Pressbooks supports open publishing practices.

Introduction to Research Methods

5 Inductive Approaches to Research

In addition to considering paradigms, researchers must also give thought to whether or not they plan to employ an inductive or a deductive approach.  While each approach is quite different, they can also be complementary.  In the following sections we will examine how these approaches are similar and dissimilar.

An inductive approach to research begins by collecting data that is relevant to the topic of interest. Once a substantial amount of data has been collected, the researcher will then take a breather from data collection, stepping back to get a bird’s eye view of the data. At this stage, the researcher looks for patterns in the data, working to develop a theory that could explain those patterns. Thus, when researchers take an inductive approach, they start with a set of observations and then they move from those particular experiences to a more general set of propositions about those experiences. In other words, they move from data to theory, or from the specific to the general (see Figure 1.4).

Text Attributions:

• This chapter has been adapted from Chapter 2.3 in Principles of Sociological Inquiry , which was adapted by the Saylor Academy without attribution to the original authors or publisher, as requested by the licensor. © Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License .

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Inductive and Deductive Reasoning — Strategic approach for conducting research

Karl questioned his research approach before finalizing the hypothesis of his research study. He laid a plan and a procedure that consists of steps of broad assumptions to detailed methods of data collection, analysis, and interpretation, wondering how to reason with your findings!

His supervisor provided him the insights about understanding his role in driving the research question by developing a research approach. The supervisor quoted, “In all the disciplines, research plays an essential role in allowing researchers to expand their theoretical knowledge in the field of their study to verify and justify the existing theories. A well-planned research approach will assist one in understanding and building a relationship between theory and objective of the research study.”

Obediently, Karl jotted down the keywords to research on the internet, understand the reasoning, and define the research approach for his research study.

Table of Contents

What Is a Research Approach?

A research approach is a procedure selected by a researcher to collect, analyze, and interpret data. Based on the methods of data collection and data analysis, research approach methods are of three types: quantitative, qualitative, and mixed methods. However, considering the general plan and procedure for conducting a study, the research approach is divided into three categories:

1. Inductive Approach

The inductive approach begins with a researcher collecting data that is relevant to the research study. Post-data collection, a researcher will analyze this data broadly, looking for patterns in the data to develop a theory that could explain the patterns. Therefore, an inductive approach starts with a set of observations and then moves toward developing a theory.

2. Deductive Approach

The deductive approach is the reverse of the inductive approach. It always starts with a theory, such as one or more general statements or premises, and reaches a logical conclusion. Scientists use this type of reasoning approach to prove their research hypothesis .

3. Abductive Approach

This type of reasoning approach is set to answer the weakness associated with deductive and inductive approaches. While following the abductive reasoning approach, researchers start the process with surprising facts or puzzles while studying some empirical phenomena which cannot be explained with the existing theories. Abductive reasoning will assist researchers in explaining the facts or puzzles. Despite its popularity, the abductive approach is challenging to implement and researchers are advised to use traditional deductive or inductive approaches.

Inductive Vs Deductive Reasoning  

What Is Inductive Reasoning?

Inductive reasoning moves away from more specific observations to broader generalizations and theories. Usually, this is against the scientific method, an empirical method of acquiring results based on experimental findings. Inductive reasoning makes generalizations by observing patterns and drawing inferences.

Inductive reasoning is based on strong and weak arguments. When the premise is true then the conclusion of the argument is likely to be true. Such an argument is termed a strong or cogent argument. Meanwhile, weak arguments may be false even if the premises they are based upon are true. An argument is a cogent argument if it is weak or the premise is false.

Types of Inductive Reasoning

1. inductive generalization.

Inductive generalization uses observations about a sample to conclude the population from which the sample was chosen. In simple terms, you use statistical results from samples to make statements about populations. One can evaluate large samples or random sampling using inductive generalizations.

2. Statistical Generalization

Statistical generalization uses specific numbers to create statements about populations. This generalization is a subtype of inductive generalization, and it is also termed statistical syllogism.

3. Causal Reasoning

Causal reasoning links cause and effect between different aspects of the research study. A casual reasoning statement starts with a premise about two events that occur simultaneously, followed by choosing a specific direction of causality or refuting any other direction, and concluding a causal statement about the relationship between two things.

4. Sign Reasoning

Sign reasoning makes correlational connections between different things. Inductive reasoning works on a correlational relationship where nothing causes the other thing to occur. However, sign reasoning proposes that one event may be a ‘sign’ to impact another event’s occurrence.

5. Analogical Reasoning

Analogical reasoning concludes something based on its similarities to another thing. It links two things together and then concludes based on the attributes of one thing which holds for another thing. Analogical reasoning could be literal or figurative. However, literal comparison usually uses a much stronger case while reasoning.

Stages of Inductive Research Approach

• Begin with an observation
• Seek patterns in the observation
• Develop a theory or preliminary conclusion based on the patterns observed

Limitations of an Inductive Approach

A conclusion drawn based on inductive reasoning cannot be proven completely, but it can be invalidated.

What Is Deductive Reasoning?

Deductive reasoning starts with one or more general statements to derive a logical conclusion. Moreover, while conducting deductive research, a researcher starts with a theory. This theory could be derived from inductive reasoning. The approach of deductive reasoning is used to test the stated theory. If the general statement or theory is true, the conclusion derived is valid and vice-versa.

Deductive reasoning produces arguments that may be valid or invalid. If the logic is correct, conclusions flow from the general statement or theory and the arguments are valid. Researchers use deductive reasoning to prove their hypotheses. However, if there is no theory yet, then one cannot conduct deductive research.

Types of Deductive Reasoning

There are three common types of deductive reasoning:

1. Syllogism

Syllogism takes two conditional statements and forms a conclusion by combining the hypothesis of one statement with the conclusion of another. For example —

If brakes fail, the car does not stop.

If the car does not stop, it will cause an accident., therefore, brake failure causes the accident., 2. modus ponens.

Modus ponens is another type of deductive reasoning that follows a pattern that affirms the condition of the reasoning. For example —

If a person is born after 1997, then they are a Gen Z

Ryan was born in 1998., therefore, ryan belongs to gen z..

This type of reasoning affirms the previous statement. Meanwhile, the first premise sets the conditional statement to be affirmed.

3. Modus Tollens

Modus tollens is yet another type of deductive reasoning known as ‘the law of contrapositive’. It is the opposite of modus ponens because it negates the condition of the reasoning. For example —

Bruce is not a Gen Z.

Therefore, bruce was not born after 1997., stages of deductive research approach.

• Begin with an existing theory and create a problem statement
• Formulate a hypothesis based on the existing theory
• Collect and analyze data to test the hypothesis
• Decide if you could reject or accept the hypothesis

Limitations of the Deductive Approach

The conclusions drawn from deductive reasoning can only be true if the theory set in the inductive study is true and the terms are clear.

Combination of Inductive and Deductive Reasoning in Research

When researchers conduct a large research project, they begin with an inductive study. This inductive reasoning assists them in constructing an efficient working theory. Therefore, post inductive reasoning, a deductive reasoning could confirm and conclude the working theory. This helps researchers formulate a structured project and mitigates the risk of research bias in the research study.

After doing thorough research in understanding inductive and deductive reasoning, Karl concluded that:

• Inductive reasoning is known for constructing hypotheses based on existing knowledge and predictions.
• Deductive reasoning could be used to test an inductive research approach.
• People tend to rely on information that is easily accessible and available in the world. While theorizing a research hypothesis , this tendency could introduce biases in the study.
• Inductive reasoning could cause biases which can distort the proper application of inductive argument.
• A good scientific research study must be highly focused and requires both inductive and deductive research approaches.

After a few hours of focused research, Karl understood his supervisor’s approach to creating a well-planned research hypothesis for his research study. Karl dived deeper and understood that he had only touched the tip of an iceberg, and there is much more to induce and deduce before he holds his doctorate!

Have you ever encountered a situation like Karl’s? Trying to understand which research approach to use? Did you find this blog informative? Do write to us or comment below and tell us what you feel!

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• Inductive vs Deductive Research Approach (with Examples)

Inductive vs Deductive Reasoning | Difference & Examples

Published on 4 May 2022 by Raimo Streefkerk . Revised on 10 October 2022.

The main difference between inductive and deductive reasoning is that inductive reasoning aims at developing a theory while deductive reasoning aims at testing an existing theory .

Inductive reasoning moves from specific observations to broad generalisations , and deductive reasoning the other way around.

Both approaches are used in various types of research , and it’s not uncommon to combine them in one large study.

Table of contents

Inductive research approach, deductive research approach, combining inductive and deductive research, frequently asked questions about inductive vs deductive reasoning.

When there is little to no existing literature on a topic, it is common to perform inductive research because there is no theory to test. The inductive approach consists of three stages:

• A low-cost airline flight is delayed
• Dogs A and B have fleas
• Elephants depend on water to exist
• Another 20 flights from low-cost airlines are delayed
• All observed dogs have fleas
• All observed animals depend on water to exist
• Low-cost airlines always have delays
• All dogs have fleas
• All biological life depends on water to exist

Limitations of an inductive approach

A conclusion drawn on the basis of an inductive method can never be proven, but it can be invalidated.

Example You observe 1,000 flights from low-cost airlines. All of them experience a delay, which is in line with your theory. However, you can never prove that flight 1,001 will also be delayed. Still, the larger your dataset, the more reliable the conclusion.

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When conducting deductive research , you always start with a theory (the result of inductive research). Reasoning deductively means testing these theories. If there is no theory yet, you cannot conduct deductive research.

The deductive research approach consists of four stages:

• If passengers fly with a low-cost airline, then they will always experience delays
• All pet dogs in my apartment building have fleas
• All land mammals depend on water to exist
• Collect flight data of low-cost airlines
• Test all dogs in the building for fleas
• Study all land mammal species to see if they depend on water
• 5 out of 100 flights of low-cost airlines are not delayed
• 10 out of 20 dogs didn’t have fleas
• All land mammal species depend on water
• 5 out of 100 flights of low-cost airlines are not delayed = reject hypothesis
• 10 out of 20 dogs didn’t have fleas = reject hypothesis
• All land mammal species depend on water = support hypothesis

Limitations of a deductive approach

The conclusions of deductive reasoning can only be true if all the premises set in the inductive study are true and the terms are clear.

• All dogs have fleas (premise)
• Benno is a dog (premise)
• Benno has fleas (conclusion)

Many scientists conducting a larger research project begin with an inductive study (developing a theory). The inductive study is followed up with deductive research to confirm or invalidate the conclusion.

In the examples above, the conclusion (theory) of the inductive study is also used as a starting point for the deductive study.

Inductive reasoning is a bottom-up approach, while deductive reasoning is top-down.

Inductive reasoning takes you from the specific to the general, while in deductive reasoning, you make inferences by going from general premises to specific conclusions.

Inductive reasoning is a method of drawing conclusions by going from the specific to the general. It’s usually contrasted with deductive reasoning, where you proceed from general information to specific conclusions.

Inductive reasoning is also called inductive logic or bottom-up reasoning.

Deductive reasoning is a logical approach where you progress from general ideas to specific conclusions. It’s often contrasted with inductive reasoning , where you start with specific observations and form general conclusions.

Deductive reasoning is also called deductive logic.

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Home » Inductive Vs Deductive Research

Inductive Vs Deductive Research

Table of Contents

When conducting research, two main approaches are commonly used: inductive and deductive. Understanding these methods is essential for any researcher as they provide different pathways to developing and testing theories. Let’s explore what these methods entail, their unique characteristics, and how they differ from each other.

Inductive Research

Inductive research is a bottom-up approach. It begins with specific observations or real examples of events, trends, or phenomena. From these specific instances, researchers look for patterns and regularities. Over time, these observations can lead to broader generalizations and theories.

For example, if a researcher observes that many students who eat breakfast perform better in school, they might develop a theory that breakfast improves academic performance. Inductive research is often exploratory and open-ended, allowing for new theories to emerge from the data.

Deductive Research

Deductive research, on the other hand, is a top-down approach. It starts with a general theory or hypothesis and then tests this theory by collecting and examining specific data. Researchers begin with an existing theory or assumption and design experiments or studies to test whether this theory holds true in particular instances.

For example, if a researcher starts with the theory that “exercise improves mental health,” they would collect data to test this hypothesis. They might conduct a study where participants are divided into groups that either do or do not exercise and then measure their mental health outcomes. Deductive research is often more focused and aims to confirm or disprove existing theories.

Difference between Inductive and Deductive Research

Here are some key differences between inductive and deductive research:

Starting Point:

• Inductive: Begins with specific observations or data.
• Deductive: Begins with a general theory or hypothesis.
• Inductive: Looks for patterns and develops a theory.
• Deductive: Tests a theory by collecting and analyzing specific data.
• Inductive: Generates new theories or ideas.
• Deductive: Confirms or refutes existing theories.
• Inductive: More open-ended and exploratory.
• Deductive: More focused and aimed at testing specific hypotheses.

Both inductive and deductive research methods are valuable in the field of research. Inductive research is useful for developing new theories, while deductive research is essential for testing and validating existing theories. By understanding and applying these methods appropriately, researchers can effectively contribute to their fields and build a solid foundation of knowledge.

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2.3: Inductive or Deductive? Two Different Approaches

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Learning Objectives

• Describe the inductive approach to research, and provide examples of inductive research.
• Describe the deductive approach to research, and provide examples of deductive research.
• Describe the ways that inductive and deductive approaches may be complementary.

Theories structure and inform sociological research. So, too, does research structure and inform theory. The reciprocal relationship between theory and research often becomes evident to students new to these topics when they consider the relationships between theory and research in inductive and deductive approaches to research. In both cases, theory is crucial. But the relationship between theory and research differs for each approach. Inductive and deductive approaches to research are quite different, but they can also be complementary. Let’s start by looking at each one and how they differ from one another. Then we’ll move on to thinking about how they complement one another.

Inductive Approaches and Some Examples

In an inductive approach to research, a researcher begins by collecting data that is relevant to his or her topic of interest. Once a substantial amount of data have been collected, the researcher will then take a breather from data collection, stepping back to get a bird’s eye view of her data. At this stage, the researcher looks for patterns in the data, working to develop a theory that could explain those patterns. Thus when researchers take an inductive approach, they start with a set of observations and then they move from those particular experiences to a more general set of propositions about those experiences. In other words, they move from data to theory, or from the specific to the general. Figure 2.5 outlines the steps involved with an inductive approach to research.

Figure 2.5 Inductive Research

There are many good examples of inductive research, but we’ll look at just a few here. One fascinating recent study in which the researchers took an inductive approach was Katherine Allen, Christine Kaestle, and Abbie Goldberg’s study (2011)Allen, K. R., Kaestle, C. E., & Goldberg, A. E. (2011). More than just a punctuation mark: How boys and young men learn about menstruation. Journal of Family Issues, 32 , 129–156. of how boys and young men learn about menstruation. To understand this process, Allen and her colleagues analyzed the written narratives of 23 young men in which the men described how they learned about menstruation, what they thought of it when they first learned about it, and what they think of it now. By looking for patterns across all 23 men’s narratives, the researchers were able to develop a general theory of how boys and young men learn about this aspect of girls’ and women’s biology. They conclude that sisters play an important role in boys’ early understanding of menstruation, that menstruation makes boys feel somewhat separated from girls, and that as they enter young adulthood and form romantic relationships, young men develop more mature attitudes about menstruation.

In another inductive study, Kristin Ferguson and colleagues (Ferguson, Kim, & McCoy, 2011)Ferguson, K. M., Kim, M. A., & McCoy, S. (2011). Enhancing empowerment and leadership among homeless youth in agency and community settings: A grounded theory approach. Child and Adolescent Social Work Journal, 28 , 1–22. analyzed empirical data to better understand how best to meet the needs of young people who are homeless. The authors analyzed data from focus groups with 20 young people at a homeless shelter. From these data they developed a set of recommendations for those interested in applied interventions that serve homeless youth. The researchers also developed hypotheses for people who might wish to conduct further investigation of the topic. Though Ferguson and her colleagues did not test the hypotheses that they developed from their analysis, their study ends where most deductive investigations begin: with a set of testable hypotheses.

Deductive Approaches and Some Examples

Researchers taking a deductive approach take the steps described earlier for inductive research and reverse their order. They start with a social theory that they find compelling and then test its implications with data. That is, they move from a more general level to a more specific one. A deductive approach to research is the one that people typically associate with scientific investigation. The researcher studies what others have done, reads existing theories of whatever phenomenon he or she is studying, and then tests hypotheses that emerge from those theories. Figure 2.6 outlines the steps involved with a deductive approach to research.

Figure 2.6 Deductive Research

While not all researchers follow a deductive approach, as you have seen in the preceding discussion, many do, and there are a number of excellent recent examples of deductive research. We’ll take a look at a couple of those next.

In a study of US law enforcement responses to hate crimes, Ryan King and colleagues (King, Messner, & Baller, 2009)King, R. D., Messner, S. F., & Baller, R. D. (2009). Contemporary hate crimes, law enforcement, and the legacy of racial violence. American Sociological Review, 74 , 291–315.hypothesized that law enforcement’s response would be less vigorous in areas of the country that had a stronger history of racial violence. The authors developed their hypothesis from their reading of prior research and theories on the topic. Next, they tested the hypothesis by analyzing data on states’ lynching histories and hate crime responses. Overall, the authors found support for their hypothesis.

In another recent deductive study, Melissa Milkie and Catharine Warner (2011)Milkie, M. A., & Warner, C. H. (2011). Classroom learning environments and the mental health of first grade children. Journal of Health and Social Behavior, 52 , 4–22. studied the effects of different classroom environments on first graders’ mental health. Based on prior research and theory, Milkie and Warner hypothesized that negative classroom features, such as a lack of basic supplies and even heat, would be associated with emotional and behavioral problems in children. The researchers found support for their hypothesis, demonstrating that policymakers should probably be paying more attention to the mental health outcomes of children’s school experiences, just as they track academic outcomes (American Sociological Association, 2011).The American Sociological Association wrote a press release on Milkie and Warner’s findings: American Sociological Association. (2011). Study: Negative classroom environment adversely affects children’s mental health. Retrieved from asanet.org/press/Negative_Cla...tal_Health.cfm

Complementary Approaches?

While inductive and deductive approaches to research seem quite different, they can actually be rather complementary. In some cases, researchers will plan for their research to include multiple components, one inductive and the other deductive. In other cases, a researcher might begin a study with the plan to only conduct either inductive or deductive research, but then he or she discovers along the way that the other approach is needed to help illuminate findings. Here is an example of each such case.

In the case of my collaborative research on sexual harassment, we began the study knowing that we would like to take both a deductive and an inductive approach in our work. We therefore administered a quantitative survey, the responses to which we could analyze in order to test hypotheses, and also conducted qualitative interviews with a number of the survey participants. The survey data were well suited to a deductive approach; we could analyze those data to test hypotheses that were generated based on theories of harassment. The interview data were well suited to an inductive approach; we looked for patterns across the interviews and then tried to make sense of those patterns by theorizing about them.

For one paper (Uggen & Blackstone, 2004),Uggen, C., & Blackstone, A. (2004). Sexual harassment as a gendered expression of power. American Sociological Review, 69 , 64–92. we began with a prominent feminist theory of the sexual harassment of adult women and developed a set of hypotheses outlining how we expected the theory to apply in the case of younger women’s and men’s harassment experiences. We then tested our hypotheses by analyzing the survey data. In general, we found support for the theory that posited that the current gender system, in which heteronormative men wield the most power in the workplace, explained workplace sexual harassment—not just of adult women but of younger women and men as well. In a more recent paper (Blackstone, Houle, & Uggen, 2006),Blackstone, A., Houle, J., & Uggen, C. “At the time I thought it was great”: Age, experience, and workers’ perceptions of sexual harassment. Presented at the 2006 meetings of the American Sociological Association. Currently under review. we did not hypothesize about what we might find but instead inductively analyzed the interview data, looking for patterns that might tell us something about how or whether workers’ perceptions of harassment change as they age and gain workplace experience. From this analysis, we determined that workers’ perceptions of harassment did indeed shift as they gained experience and that their later definitions of harassment were more stringent than those they held during adolescence. Overall, our desire to understand young workers’ harassment experiences fully—in terms of their objective workplace experiences, their perceptions of those experiences, and their stories of their experiences—led us to adopt both deductive and inductive approaches in the work.

Researchers may not always set out to employ both approaches in their work but sometimes find that their use of one approach leads them to the other. One such example is described eloquently in Russell Schutt’s Investigating the Social World (2006).Schutt, R. K. (2006). Investigating the social world: The process and practice of research . Thousand Oaks, CA: Pine Forge Press. As Schutt describes, researchers Lawrence Sherman and Richard Berk (1984)Sherman, L. W., & Berk, R. A. (1984). The specific deterrent effects of arrest for domestic assault. American Sociological Review, 49 , 261–272. conducted an experiment to test two competing theories of the effects of punishment on deterring deviance (in this case, domestic violence). Specifically, Sherman and Berk hypothesized that deterrence theory would provide a better explanation of the effects of arresting accused batterers than labeling theory . Deterrence theory predicts that arresting an accused spouse batterer will reduce future incidents of violence. Conversely, labeling theory predicts that arresting accused spouse batterers will increase future incidents. Figure 2.7 summarizes the two competing theories and the predictions that Sherman and Berk set out to test.

Figure 2.7 Predicting the Effects of Arrest on Future Spouse Battery

Sherman and Berk found, after conducting an experiment with the help of local police in one city, that arrest did in fact deter future incidents of violence, thus supporting their hypothesis that deterrence theory would better predict the effect of arrest. After conducting this research, they and other researchers went on to conduct similar experimentsThe researchers did what’s called replication. We’ll learn more about replication in Chapter 3. in six additional cities (Berk, Campbell, Klap, & Western, 1992; Pate & Hamilton, 1992; Sherman & Smith, 1992).Berk, R., Campbell, A., Klap, R., & Western, B. (1992). The deterrent effect of arrest in incidents of domestic violence: A Bayesian analysis of four field experiments. American Sociological Review, 57 , 698–708; Pate, A., & Hamilton, E. (1992). Formal and informal deterrents to domestic violence: The Dade county spouse assault experiment. American Sociological Review, 57 , 691–697; Sherman, L., & Smith, D. (1992). Crime, punishment, and stake in conformity: Legal and informal control of domestic violence. American Sociological Review, 57 , 680–690. Results from these follow-up studies were mixed. In some cases, arrest deterred future incidents of violence. In other cases, it did not. This left the researchers with new data that they needed to explain. The researchers therefore took an inductive approach in an effort to make sense of their latest empirical observations. The new studies revealed that arrest seemed to have a deterrent effect for those who were married and employed but that it led to increased offenses for those who were unmarried and unemployed. Researchers thus turned to control theory, which predicts that having some stake in conformity through the social ties provided by marriage and employment, as the better explanation.

Figure 2.8 Predicting the Effects of Arrest on Future Spouse Battery: A New Theory

What the Sherman and Berk research, along with the follow-up studies, shows us is that we might start with a deductive approach to research, but then, if confronted by new data that we must make sense of, we may move to an inductive approach. Russell Schutt depicts this process quite nicely in his text, and I’ve adapted his depiction here, in Figure 2.9.

KEY TAKEAWAYS

• The inductive approach involves beginning with a set of empirical observations, seeking patterns in those observations, and then theorizing about those patterns.
• The deductive approach involves beginning with a theory, developing hypotheses from that theory, and then collecting and analyzing data to test those hypotheses.
• Inductive and deductive approaches to research can be employed together for a more complete understanding of the topic that a researcher is studying.
• Though researchers don’t always set out to use both inductive and deductive strategies in their work, they sometimes find that new questions arise in the course of an investigation that can best be answered by employing both approaches.

Monty Python and Holy Grail :

(click to see video)

Do the townspeople take an inductive or deductive approach to determine whether the woman in question is a witch? What are some of the different sources of knowledge (recall Chapter 1) they rely on?

• Think about how you could approach a study of the relationship between gender and driving over the speed limit. How could you learn about this relationship using an inductive approach? What would a study of the same relationship look like if examined using a deductive approach? Try the same thing with any topic of your choice. How might you study the topic inductively? Deductively?

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Inductive vs Deductive Research: Difference of Approaches

The terms “inductive” and “deductive” are often used in logic, reasoning, and science. Scientists use both inductive and deductive research methods as part of the scientific method.

Famous fictional detectives like Sherlock Holmes are often associated with deduction, even though that’s not always what Holmes does (more on that later). Some writing classes include both inductive and deductive essays.

But what’s the difference between inductive vs deductive research? The difference often lies in whether the argument proceeds from the general to the specific or the specific to the general. 

Both methods are used in different types of research, and it’s not unusual to use both in one project. In this article, we’ll describe each in simple yet defined terms.

Content Index: 

What is inductive research, stages of inductive research process, what is deductive research, stages of deductive research process, difference between inductive vs deductive research.

Inductive research is a method in which the researcher collects and analyzes data to develop theories, concepts, or hypotheses based on patterns and observations seen in the data. 

It uses a “bottom-up” method in which the researcher starts with specific observations and then moves on to more general theories or ideas. Inductive research is often used in exploratory studies or when not much research has been done on a topic before.

LEARN ABOUT: Research Process Steps

The three steps of the inductive research process are:

• Observation: 

The first step of inductive research is to make detailed observations of the studied phenomenon. This can be done in many ways, such as through surveys, interviews, or direct observation.

• Pattern Recognition: 

The next step is to look at the data in detail once the data has been collected. This means looking at the data for patterns, themes, and relationships. The goal is to find insights and trends that can be used to make the first categories and ideas.

• Theory Development: 

At this stage, the researcher will start to create initial categories or concepts based on the patterns and themes from the data analysis. This means putting the data into groups based on their similarities and differences to make a framework for understanding the thing being studied.

LEARN ABOUT: Data Management Framework

These three steps are often repeated in a cycle, so the researcher can improve their analysis and understand the phenomenon over time. Inductive research aims to develop new theories and ideas based on the data rather than testing existing theories, as in deductive research.

Deductive research is a type of research in which the researcher starts with a theory, hypothesis, or generalization and then tests it through observations and data collection.

It uses a top-down method in which the researcher starts with a general idea and then tests it through specific observations. Deductive research is often used to confirm a theory or test a well-known hypothesis.

The five steps in the process of deductive research are:

• Formulation of a hypothesis: 

The first step in deductive research is to develop a hypothesis and guess how the variables are related. Most of the time, the hypothesis is built on theories or research that have already been done.

• Design of a research study: 

The next step is designing a research study to test the hypothesis. This means choosing a research method, figuring out what needs to be measured, and figuring out how to collect and look at the data.

• Collecting data: 

Once the research design is set, different methods, such as surveys, experiments, or observational studies, are used to gather data. Usually, a standard protocol is used to collect the data to ensure it is correct and consistent.

• Analysis of data: 

In this step, the collected data are looked at to see if they support or disprove the hypothesis. The goal is to see if the data supports or refutes the hypothesis. You need to use statistical methods to find patterns and links between the variables to do this.

• Drawing conclusions: 

The last step is drawing conclusions from the analysis of the data. If the hypothesis is supported, it can be used to make generalizations about the population being studied. If the hypothesis is wrong, the researcher may need to develop a new one and start the process again.

The five steps of deductive research are repeated, and researchers may need to return to earlier steps if they find new information or new ways of looking at things. In contrast to inductive research, deductive research aims to test theories or hypotheses that have already been made.

The main differences between inductive and deductive research are how the research is done, the goal, and how the data is analyzed. Inductive research is exploratory, flexible, and based on qualitative observation analysis. Deductive research, on the other hand, is about proving something and is structured and based on quantitative analysis .

Here are the main differences between inductive vs deductive research in more detail:

LEARN ABOUT: Theoretical Research

Inductive research and deductive research are two different types of research with different starting points, goals, methods, and ways of looking at the data.

Inductive research uses specific observations and patterns to come up with new theories. On the other hand, deductive research starts with a theory or hypothesis and tests it through observations.

Both approaches have advantages as well as disadvantages and can be used in different types of research depending on the question and goals.

QuestionPro is a responsive online platform for surveys and research that can be used for both inductive and deductive research. It has many tools and features to help you collect and analyze data, such as customizable survey templates, advanced survey logic, and real-time reporting.

With QuestionPro, researchers can do surveys, send them out, analyze the results, and draw conclusions that help them make decisions and learn more about their fields.

The platform has advanced data analysis and reporting tools that can be used with both qualitative and quantitative methods of data analysis.

Whether researchers do inductive or deductive research, QuestionPro can help them design, run, and analyze their projects completely and powerfully. So sign up now for a free trial! 

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• Inductive Research: What It Is, Benefits & When to Use

You’ve probably heard or seen “inductive research” and “deductive research” countless times as a researcher. These are two different research methods that have their perks and downsides. 

Inductive research collects and analyzes data to identify patterns and themes which function as the basis for a theory or hypothesis. Deductive research, on the other hand, involves developing a theory or hypothesis and testing it through empirical data collection and analysis.

In this article, we will focus on inductive research, its examples, and when to use it.

What Is Inductive Research?

Inductive research is also known as bottom-up or data-driven research. It’s exploratory and qualitative; the focus is on understanding the experiences, attitudes, and beliefs of individuals or groups.

So, inductive research does not rely on numerical data but uses qualitative data such as words, images, or videos. It’s also very flexible, allowing you to adjust the research questions or methods as the data emerges.

The main goal of inductive research is to discover new patterns, relationships, or phenomena that are not explained by existing theories or knowledge. It starts with specific observations and then moves to general conclusions.

So, you start the research with an open mind and collect data without any preconceived theories or hypotheses. Next, you analyze the data to identify patterns, themes, and relationships.

Related: What is Deductive Research? Meaning, Stages & Examples

Examples of Inductive Research

You can apply inductive research to various fields such as sociology, psychology, education, marketing, and more. Here are some examples of inductive research:

Research Question- How Do Different Demographics Cope With Stress?

You’re a sociologist that wants to understand how people cope with stress in their everyday lives. The first step is to interview people from different backgrounds and ask them about their sources of stress and coping mechanisms.

Next, analyze the interview manuscripts to identify common themes and patterns among the responses. Finally, use the themes to develop a theory of how different demographic cope with stress.

Do Social Media Influencers Impact Consumer Behavior?

This is qualitative and quantitative research. Start by performing a content analysis of social media posts by influencers and their followers, as well as a survey of consumers who follow influencers online. 

Next, integrate the results from both methods and derive a comprehensive understanding of how influencers influence consumer behavior.

What are the Effects of Video Games on Children’s Behavior?

You observe a group of children playing different types of video games for a certain period and record their actions and interactions. Next, compare the children’s behavior- children who played violent games versus those who played non-violent games. 

Use the observation to formulate a hypothesis about the relationship between video game violence and aggression.

Research Question- Why are the majority of students more successful in a particular course than others?

Start by observing the students in class, interviewing them, and reviewing their test scores.

Next, analyze the data to identify patterns and themes. Based on this analysis, the teacher develops a theory that explains the factors that contribute to student success in that subject.

Research Question- What factors influence a product’s customer loyalty? 

You can investigate the factors that influence customers’ purchasing decisions. Start by sampling return and long-term customers, and asks them about what makes them want to stick with your brand.

Next, analyze the survey to identify the variables that influences customer loyalty. These variables can help you understand your customer pain points, which gives you a significant competitive advantage.

Stages of Inductive Research

Inductive research typically follows four main stages:

• Data collection : collect relevant data from various sources, such as interviews, surveys, observations, documents, etc. Ensure the data is detailed enough to allow for meaningful analysis, and collected without any preconceived theories or hypotheses.
• Data analysis : analyze the data to identify patterns, trends, themes, or categories that emerge from the data. You can use various techniques such as grounded theory, memoing, or thematic analysis to organize and interpret the data.
• Theory generation : develop a theory or a hypothesis that explains the data. The theory should be based on the data and reflect the reality of the phenomenon under study.
• Theory verification : test the validity and reliability of the theory or hypothesis using additional data or methods. You can use deductive reasoning or quantitative methods to confirm or reject the theory or hypothesis.

Uses of Inductive Research and When to Use It

Inductive research is majorly used to explore new topics or phenomena that are not well understood or explained by existing theories or knowledge. 

Here are some common uses cases: 

• Generating new insights and perspectives on a phenomenon
• Discovering new concepts or variables that are relevant to a phenomenon
• Developing new theories or hypotheses that can be tested empirically
• Improving creativity and innovation skills
• Understanding and appreciating diversity and complexity

When should you use inductive research:

• The vague research question that needs to be refined or narrowed down
• Limited or no prior knowledge or assumptions about a phenomenon
• When investigating a phenomenon in its natural context or setting
• Collecting adaptable or situational data

Benefits of Inductive Research

• Flexible and Adaptable Research Method

Since inductive research does not start with a fixed theory, it can adjust to new findings and insights that emerge from the data. For example, if you’re studying customer preferences for a new product, you can use inductive research to discover unexpected patterns or trends that might not fit into an existing theory.

• Creative and Innovative

Inductive research encourages you to identify new connections and explanations that can lead to new theories and hypotheses. Let’s say you’re studying the causes of climate change, you can use inductive research to identify new factors or variables that other researchers overlook.

• Data-Driven

Inductive research relies on data and evidence to support its conclusions, rather than on assumptions or logic. As a result, inductive research is more credible and valid because it reflects the reality of the problem or situation.

For example, if a researcher is studying the effects of social media on mental health, they can use inductive research to base their arguments on actual data from surveys or experiments.

How Does Formplus Help in Inductive Research?

Formplus is a data collection tool that allows you to create and administer online surveys for inductive research effortlessly. With Formplus, you can design customized surveys with different question types and conditional logic to fit your research objectives.

You can also easily your data using Formplus analytics or export to a third-party data analysis tool.

Perks of Using Formplus for Inductive Research:

• Dynamic and Customizable Surveys

You can create surveys with different question types, such as text, number, rating, multiple choice, single choice, image choice, file upload, signature, and more. You can also use logic features such as skip logic, validation rules, calculations, and conditional logic to make your surveys more interactive and relevant to your respondents.

• Seamless Data Collection

You can easily distribute your surveys to your target audience by email, social media, QR code, or embedding them on your website. Formplus also has an offline form feature that allows you to collect data without an internet connection and syncs when you are online.

• Data Security

You can collect data from various sources and store it securely in Formplus cloud storage or your preferred cloud storage. If you’d like to perform further analysis, you can export the data in different formats such as PDF, CSV, Excel, or Doc.

• In-app Data Analysis 

You can analyze your data using Formplus analytics or integrate with third-party tools such as Google Sheets, Tableau, Power BI, or Zapier. You can also generate reports and charts to visualize your data and discover patterns and trends.

• Team Collaboration

Using Formplus team features, you can collaborate on your surveys and data with your team members and stakeholders. You can assign roles and permissions, add comments, track changes, and share feedback on your surveys and data.

Inductive research is an open-minded method for researching new topics. When done properly, you can use it to explain complex concepts and identify relationships or patterns between variables.

Using a powerful tool like Formplus allows you to conduct inductive research effectively. Sign up for a free trial and create your inductive research survey in minutes!

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• inductive research
• inductive vs deductive research
• numerical data
• qualitative data
• research surveys
• Moradeke Owa

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2.3 Inductive and deductive reasoning

Learning objectives.

• Describe the inductive approach to research, and provide examples of inductive research
• Describe the deductive approach to research, and provide examples of deductive research
• Describe the ways that inductive and deductive approaches may be complementary

Theories structure and inform social work research. So, too, does research structure and inform theory. The reciprocal relationship between theory and research often becomes evident to students new to these topics when they consider the relationships between theory and research in inductive and deductive approaches to research. In both cases, theory is crucial. But the relationship between theory and research differs for each approach.

Inductive and deductive approaches to research are quite different, but they can also be complementary. Let’s start by looking at each one and how they differ from one another. Then we’ll move on to thinking about how they complement one another.

Inductive approaches and some examples

In an inductive approach to research, a researcher begins by collecting data that is relevant to her topic of interest. Once a substantial amount of data have been collected, the researcher will then take a breather from data collection, stepping back to get a bird’s eye view of their data. At this stage, the researcher looks for patterns in the data, working to develop a theory that could explain those patterns. Thus, when researchers take an inductive approach, they start with a set of observations and then they move from those particular experiences to a more general set of propositions about those experiences. In other words, they move from data to theory, or from the specific to the general. Figure 6.1 outlines the steps involved with an inductive approach to research.

There are many good examples of inductive research, but we’ll look at just a few here. One fascinating study in which the researchers took an inductive approach is Katherine Allen, Christine Kaestle, and Abbie Goldberg’s (2011) study of how boys and young men learn about menstruation. To understand this process, Allen and her colleagues analyzed the written narratives of 23 young men in which the men described how they learned about menstruation, what they thought of it when they first learned about it, and what they think of it now. By looking for patterns across all 23 men’s narratives, the researchers were able to develop a general theory of how boys and young men learn about this aspect of girls’ and women’s biology. They conclude that sisters play an important role in boys’ early understanding of menstruation, that menstruation makes boys feel somewhat separated from girls, and that as they enter young adulthood and form romantic relationships, young men develop more mature attitudes about menstruation. Note how this study began with the data—men’s narratives of learning about menstruation—and tried to develop a theory.

In another inductive study, Kristin Ferguson and colleagues (Ferguson, Kim, & McCoy, 2011) analyzed empirical data to better understand how best to meet the needs of young people who are homeless. The authors analyzed data from focus groups with 20 young people at a homeless shelter. From these data they developed a set of recommendations for those interested in applied interventions that serve homeless youth. The researchers also developed hypotheses for people who might wish to conduct further investigation of the topic. Though Ferguson and her colleagues did not test the hypotheses that they developed from their analysis, their study ends where most deductive investigations begin: with a theory and a hypothesis derived from that theory.

Deductive approaches and some examples

Researchers taking a deductive approach take the steps described earlier for inductive research and reverse their order. They start with a social theory that they find compelling and then test its implications with data. That is, they move from a more general level to a more specific one. A deductive approach to research is the one that people typically associate with scientific investigation. The researcher studies what others have done, reads existing theories of whatever phenomenon she is studying, and then tests hypotheses that emerge from those theories. Figure 2.2 outlines the steps involved with a deductive approach to research.

While not all researchers follow a deductive approach, as you have seen in the preceding discussion, many do, and there are a number of excellent recent examples of deductive research. We’ll take a look at a couple of those next.

In a study of United States law enforcement responses to hate crimes, Ryan King and colleagues (King, Messner, & Baller, 2009) hypothesized that law enforcement’s response would be less vigorous in areas of the country that had a stronger history of racial violence. The authors developed their hypothesis from their reading of prior research and theories on the topic. They tested the hypothesis by analyzing data on states’ lynching histories and hate crime responses. Overall, the authors found support for their hypothesis. One might associate this research with critical theory.

In another recent deductive study, Melissa Milkie and Catharine Warner (2011) studied the effects of different classroom environments on first graders’ mental health. Based on prior research and theory, Milkie and Warner hypothesized that negative classroom features, such as a lack of basic supplies and even heat, would be associated with emotional and behavioral problems in children. One might associate this research with systems theory. The researchers found support for their hypothesis, demonstrating that policymakers should probably be paying more attention to the mental health outcomes of children’s school experiences, just as they track academic outcomes (American Sociological Association, 2011).

Complementary approaches

While inductive and deductive approaches to research seem quite different, they can actually be rather complementary. In some cases, researchers will plan for their study to include multiple components, one inductive and the other deductive. In other cases, a researcher might begin a study with the plan to only conduct either inductive or deductive research, but then discovers along the way that the other approach is needed to help illuminate findings.

Researchers may not always set out to employ both approaches in their work but sometimes find that their use of one approach leads them to the other. One such example is described eloquently in Russell Schutt’s Investigating the Social World (2006). As Schutt describes, researchers Lawrence Sherman and Richard Berk (1984) conducted an experiment to test two competing theories of the effects of punishment on deterring deviance (in this case, domestic violence). Specifically, Sherman and Berk hypothesized that deterrence theory would provide a better explanation of the effects of arresting accused batterers than labeling theory . Deterrence theory predicts that arresting an accused spouse batterer will reduce future incidents of violence. Conversely, labeling theory predicts that arresting accused spouse batterers will increase future incidents. Figure 2.3 summarizes the two competing theories and the predictions that Sherman and Berk set out to test.

Sherman and Berk found, after conducting an experiment with the help of local police in one city, that arrest did in fact deter future incidents of violence, thus supporting their hypothesis that deterrence theory would better predict the effect of arrest. After conducting this research, they and other researchers did what is called replication and went on to conduct similar experiments in six additional cities (Berk, Campbell, Klap, & Western, 1992; Pate & Hamilton, 1992; Sherman & Smith, 1992). Results from these follow-up studies were mixed. In some cases, arrest deterred future incidents of violence. In other cases, it did not. This left the researchers with new data that they needed to explain. The researchers therefore took an inductive approach in an effort to make sense of their latest empirical observations. The new studies revealed that arrest seemed to have a deterrent effect for those who were married and employed, but that it led to increased offenses for those who were unmarried and unemployed. Researchers thus turned to control theory, which predicts that having some stake in conformity through the social ties provided by marriage and employment, as the better explanation.

What the Sherman and Berk research, along with the follow-up studies, shows us is that we might start with a deductive approach to research, but then, if confronted by new data that we must make sense of, we may move to an inductive approach.

Key Takeaways

• The inductive approach begins with a set of empirical observations, seeking patterns in those observations, and then theorizing about those patterns.
• The deductive approach begins with a theory, developing hypotheses from that theory, and then collecting and analyzing data to test those hypotheses.
• Inductive and deductive approaches to research can be employed together for a more complete understanding of the topic that a researcher is studying.
• Though researchers don’t always set out to use both inductive and deductive strategies in their work, they sometimes find that new questions arise in the course of an investigation that can best be answered by employing both approaches.
• Deductive approach- study what others have done, reads existing theories of whatever phenomenon she is studying, and then tests hypotheses that emerge from those theories
• Inductive approach- start with a set of observations and then move from particular experiences to a more general set of propositions about those experiences

Image Attributions

All figures in this section are copied from Blackstone, A. (2012) Principles of sociological inquiry: Qualitative and quantitative methods. Saylor Foundation. Retrieved from: https://saylordotorg.github.io/text_principles-of-sociological-inquiry-qualitative-and-quantitative-methods/ Shared under CC-BY-NC-SA 3.0 License

Foundations of Social Work Research Copyright © 2020 by Rebecca L. Mauldin is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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A Practical Guide to Writing Quantitative and Qualitative Research Questions and Hypotheses in Scholarly Articles

Edward barroga.

1 Department of General Education, Graduate School of Nursing Science, St. Luke’s International University, Tokyo, Japan.

Glafera Janet Matanguihan

2 Department of Biological Sciences, Messiah University, Mechanicsburg, PA, USA.

The development of research questions and the subsequent hypotheses are prerequisites to defining the main research purpose and specific objectives of a study. Consequently, these objectives determine the study design and research outcome. The development of research questions is a process based on knowledge of current trends, cutting-edge studies, and technological advances in the research field. Excellent research questions are focused and require a comprehensive literature search and in-depth understanding of the problem being investigated. Initially, research questions may be written as descriptive questions which could be developed into inferential questions. These questions must be specific and concise to provide a clear foundation for developing hypotheses. Hypotheses are more formal predictions about the research outcomes. These specify the possible results that may or may not be expected regarding the relationship between groups. Thus, research questions and hypotheses clarify the main purpose and specific objectives of the study, which in turn dictate the design of the study, its direction, and outcome. Studies developed from good research questions and hypotheses will have trustworthy outcomes with wide-ranging social and health implications.

INTRODUCTION

Scientific research is usually initiated by posing evidenced-based research questions which are then explicitly restated as hypotheses. 1 , 2 The hypotheses provide directions to guide the study, solutions, explanations, and expected results. 3 , 4 Both research questions and hypotheses are essentially formulated based on conventional theories and real-world processes, which allow the inception of novel studies and the ethical testing of ideas. 5 , 6

It is crucial to have knowledge of both quantitative and qualitative research 2 as both types of research involve writing research questions and hypotheses. 7 However, these crucial elements of research are sometimes overlooked; if not overlooked, then framed without the forethought and meticulous attention it needs. Planning and careful consideration are needed when developing quantitative or qualitative research, particularly when conceptualizing research questions and hypotheses. 4

There is a continuing need to support researchers in the creation of innovative research questions and hypotheses, as well as for journal articles that carefully review these elements. 1 When research questions and hypotheses are not carefully thought of, unethical studies and poor outcomes usually ensue. Carefully formulated research questions and hypotheses define well-founded objectives, which in turn determine the appropriate design, course, and outcome of the study. This article then aims to discuss in detail the various aspects of crafting research questions and hypotheses, with the goal of guiding researchers as they develop their own. Examples from the authors and peer-reviewed scientific articles in the healthcare field are provided to illustrate key points.

DEFINITIONS AND RELATIONSHIP OF RESEARCH QUESTIONS AND HYPOTHESES

A research question is what a study aims to answer after data analysis and interpretation. The answer is written in length in the discussion section of the paper. Thus, the research question gives a preview of the different parts and variables of the study meant to address the problem posed in the research question. 1 An excellent research question clarifies the research writing while facilitating understanding of the research topic, objective, scope, and limitations of the study. 5

On the other hand, a research hypothesis is an educated statement of an expected outcome. This statement is based on background research and current knowledge. 8 , 9 The research hypothesis makes a specific prediction about a new phenomenon 10 or a formal statement on the expected relationship between an independent variable and a dependent variable. 3 , 11 It provides a tentative answer to the research question to be tested or explored. 4

Hypotheses employ reasoning to predict a theory-based outcome. 10 These can also be developed from theories by focusing on components of theories that have not yet been observed. 10 The validity of hypotheses is often based on the testability of the prediction made in a reproducible experiment. 8

Conversely, hypotheses can also be rephrased as research questions. Several hypotheses based on existing theories and knowledge may be needed to answer a research question. Developing ethical research questions and hypotheses creates a research design that has logical relationships among variables. These relationships serve as a solid foundation for the conduct of the study. 4 , 11 Haphazardly constructed research questions can result in poorly formulated hypotheses and improper study designs, leading to unreliable results. Thus, the formulations of relevant research questions and verifiable hypotheses are crucial when beginning research. 12

CHARACTERISTICS OF GOOD RESEARCH QUESTIONS AND HYPOTHESES

Excellent research questions are specific and focused. These integrate collective data and observations to confirm or refute the subsequent hypotheses. Well-constructed hypotheses are based on previous reports and verify the research context. These are realistic, in-depth, sufficiently complex, and reproducible. More importantly, these hypotheses can be addressed and tested. 13

There are several characteristics of well-developed hypotheses. Good hypotheses are 1) empirically testable 7 , 10 , 11 , 13 ; 2) backed by preliminary evidence 9 ; 3) testable by ethical research 7 , 9 ; 4) based on original ideas 9 ; 5) have evidenced-based logical reasoning 10 ; and 6) can be predicted. 11 Good hypotheses can infer ethical and positive implications, indicating the presence of a relationship or effect relevant to the research theme. 7 , 11 These are initially developed from a general theory and branch into specific hypotheses by deductive reasoning. In the absence of a theory to base the hypotheses, inductive reasoning based on specific observations or findings form more general hypotheses. 10

TYPES OF RESEARCH QUESTIONS AND HYPOTHESES

Research questions and hypotheses are developed according to the type of research, which can be broadly classified into quantitative and qualitative research. We provide a summary of the types of research questions and hypotheses under quantitative and qualitative research categories in Table 1 .

Research questions in quantitative research

In quantitative research, research questions inquire about the relationships among variables being investigated and are usually framed at the start of the study. These are precise and typically linked to the subject population, dependent and independent variables, and research design. 1 Research questions may also attempt to describe the behavior of a population in relation to one or more variables, or describe the characteristics of variables to be measured ( descriptive research questions ). 1 , 5 , 14 These questions may also aim to discover differences between groups within the context of an outcome variable ( comparative research questions ), 1 , 5 , 14 or elucidate trends and interactions among variables ( relationship research questions ). 1 , 5 We provide examples of descriptive, comparative, and relationship research questions in quantitative research in Table 2 .

Hypotheses in quantitative research

In quantitative research, hypotheses predict the expected relationships among variables. 15 Relationships among variables that can be predicted include 1) between a single dependent variable and a single independent variable ( simple hypothesis ) or 2) between two or more independent and dependent variables ( complex hypothesis ). 4 , 11 Hypotheses may also specify the expected direction to be followed and imply an intellectual commitment to a particular outcome ( directional hypothesis ) 4 . On the other hand, hypotheses may not predict the exact direction and are used in the absence of a theory, or when findings contradict previous studies ( non-directional hypothesis ). 4 In addition, hypotheses can 1) define interdependency between variables ( associative hypothesis ), 4 2) propose an effect on the dependent variable from manipulation of the independent variable ( causal hypothesis ), 4 3) state a negative relationship between two variables ( null hypothesis ), 4 , 11 , 15 4) replace the working hypothesis if rejected ( alternative hypothesis ), 15 explain the relationship of phenomena to possibly generate a theory ( working hypothesis ), 11 5) involve quantifiable variables that can be tested statistically ( statistical hypothesis ), 11 6) or express a relationship whose interlinks can be verified logically ( logical hypothesis ). 11 We provide examples of simple, complex, directional, non-directional, associative, causal, null, alternative, working, statistical, and logical hypotheses in quantitative research, as well as the definition of quantitative hypothesis-testing research in Table 3 .

Research questions in qualitative research

Unlike research questions in quantitative research, research questions in qualitative research are usually continuously reviewed and reformulated. The central question and associated subquestions are stated more than the hypotheses. 15 The central question broadly explores a complex set of factors surrounding the central phenomenon, aiming to present the varied perspectives of participants. 15

There are varied goals for which qualitative research questions are developed. These questions can function in several ways, such as to 1) identify and describe existing conditions ( contextual research question s); 2) describe a phenomenon ( descriptive research questions ); 3) assess the effectiveness of existing methods, protocols, theories, or procedures ( evaluation research questions ); 4) examine a phenomenon or analyze the reasons or relationships between subjects or phenomena ( explanatory research questions ); or 5) focus on unknown aspects of a particular topic ( exploratory research questions ). 5 In addition, some qualitative research questions provide new ideas for the development of theories and actions ( generative research questions ) or advance specific ideologies of a position ( ideological research questions ). 1 Other qualitative research questions may build on a body of existing literature and become working guidelines ( ethnographic research questions ). Research questions may also be broadly stated without specific reference to the existing literature or a typology of questions ( phenomenological research questions ), may be directed towards generating a theory of some process ( grounded theory questions ), or may address a description of the case and the emerging themes ( qualitative case study questions ). 15 We provide examples of contextual, descriptive, evaluation, explanatory, exploratory, generative, ideological, ethnographic, phenomenological, grounded theory, and qualitative case study research questions in qualitative research in Table 4 , and the definition of qualitative hypothesis-generating research in Table 5 .

Qualitative studies usually pose at least one central research question and several subquestions starting with How or What . These research questions use exploratory verbs such as explore or describe . These also focus on one central phenomenon of interest, and may mention the participants and research site. 15

Hypotheses in qualitative research

Hypotheses in qualitative research are stated in the form of a clear statement concerning the problem to be investigated. Unlike in quantitative research where hypotheses are usually developed to be tested, qualitative research can lead to both hypothesis-testing and hypothesis-generating outcomes. 2 When studies require both quantitative and qualitative research questions, this suggests an integrative process between both research methods wherein a single mixed-methods research question can be developed. 1

FRAMEWORKS FOR DEVELOPING RESEARCH QUESTIONS AND HYPOTHESES

Research questions followed by hypotheses should be developed before the start of the study. 1 , 12 , 14 It is crucial to develop feasible research questions on a topic that is interesting to both the researcher and the scientific community. This can be achieved by a meticulous review of previous and current studies to establish a novel topic. Specific areas are subsequently focused on to generate ethical research questions. The relevance of the research questions is evaluated in terms of clarity of the resulting data, specificity of the methodology, objectivity of the outcome, depth of the research, and impact of the study. 1 , 5 These aspects constitute the FINER criteria (i.e., Feasible, Interesting, Novel, Ethical, and Relevant). 1 Clarity and effectiveness are achieved if research questions meet the FINER criteria. In addition to the FINER criteria, Ratan et al. described focus, complexity, novelty, feasibility, and measurability for evaluating the effectiveness of research questions. 14

The PICOT and PEO frameworks are also used when developing research questions. 1 The following elements are addressed in these frameworks, PICOT: P-population/patients/problem, I-intervention or indicator being studied, C-comparison group, O-outcome of interest, and T-timeframe of the study; PEO: P-population being studied, E-exposure to preexisting conditions, and O-outcome of interest. 1 Research questions are also considered good if these meet the “FINERMAPS” framework: Feasible, Interesting, Novel, Ethical, Relevant, Manageable, Appropriate, Potential value/publishable, and Systematic. 14

As we indicated earlier, research questions and hypotheses that are not carefully formulated result in unethical studies or poor outcomes. To illustrate this, we provide some examples of ambiguous research question and hypotheses that result in unclear and weak research objectives in quantitative research ( Table 6 ) 16 and qualitative research ( Table 7 ) 17 , and how to transform these ambiguous research question(s) and hypothesis(es) into clear and good statements.

a These statements were composed for comparison and illustrative purposes only.

b These statements are direct quotes from Higashihara and Horiuchi. 16

a This statement is a direct quote from Shimoda et al. 17

The other statements were composed for comparison and illustrative purposes only.

CONSTRUCTING RESEARCH QUESTIONS AND HYPOTHESES

To construct effective research questions and hypotheses, it is very important to 1) clarify the background and 2) identify the research problem at the outset of the research, within a specific timeframe. 9 Then, 3) review or conduct preliminary research to collect all available knowledge about the possible research questions by studying theories and previous studies. 18 Afterwards, 4) construct research questions to investigate the research problem. Identify variables to be accessed from the research questions 4 and make operational definitions of constructs from the research problem and questions. Thereafter, 5) construct specific deductive or inductive predictions in the form of hypotheses. 4 Finally, 6) state the study aims . This general flow for constructing effective research questions and hypotheses prior to conducting research is shown in Fig. 1 .

Research questions are used more frequently in qualitative research than objectives or hypotheses. 3 These questions seek to discover, understand, explore or describe experiences by asking “What” or “How.” The questions are open-ended to elicit a description rather than to relate variables or compare groups. The questions are continually reviewed, reformulated, and changed during the qualitative study. 3 Research questions are also used more frequently in survey projects than hypotheses in experiments in quantitative research to compare variables and their relationships.

Hypotheses are constructed based on the variables identified and as an if-then statement, following the template, ‘If a specific action is taken, then a certain outcome is expected.’ At this stage, some ideas regarding expectations from the research to be conducted must be drawn. 18 Then, the variables to be manipulated (independent) and influenced (dependent) are defined. 4 Thereafter, the hypothesis is stated and refined, and reproducible data tailored to the hypothesis are identified, collected, and analyzed. 4 The hypotheses must be testable and specific, 18 and should describe the variables and their relationships, the specific group being studied, and the predicted research outcome. 18 Hypotheses construction involves a testable proposition to be deduced from theory, and independent and dependent variables to be separated and measured separately. 3 Therefore, good hypotheses must be based on good research questions constructed at the start of a study or trial. 12

In summary, research questions are constructed after establishing the background of the study. Hypotheses are then developed based on the research questions. Thus, it is crucial to have excellent research questions to generate superior hypotheses. In turn, these would determine the research objectives and the design of the study, and ultimately, the outcome of the research. 12 Algorithms for building research questions and hypotheses are shown in Fig. 2 for quantitative research and in Fig. 3 for qualitative research.

EXAMPLES OF RESEARCH QUESTIONS FROM PUBLISHED ARTICLES

• EXAMPLE 1. Descriptive research question (quantitative research)
• - Presents research variables to be assessed (distinct phenotypes and subphenotypes)
• “BACKGROUND: Since COVID-19 was identified, its clinical and biological heterogeneity has been recognized. Identifying COVID-19 phenotypes might help guide basic, clinical, and translational research efforts.
• RESEARCH QUESTION: Does the clinical spectrum of patients with COVID-19 contain distinct phenotypes and subphenotypes? ” 19
• EXAMPLE 2. Relationship research question (quantitative research)
• - Shows interactions between dependent variable (static postural control) and independent variable (peripheral visual field loss)
• “Background: Integration of visual, vestibular, and proprioceptive sensations contributes to postural control. People with peripheral visual field loss have serious postural instability. However, the directional specificity of postural stability and sensory reweighting caused by gradual peripheral visual field loss remain unclear.
• Research question: What are the effects of peripheral visual field loss on static postural control ?” 20
• EXAMPLE 3. Comparative research question (quantitative research)
• - Clarifies the difference among groups with an outcome variable (patients enrolled in COMPERA with moderate PH or severe PH in COPD) and another group without the outcome variable (patients with idiopathic pulmonary arterial hypertension (IPAH))
• “BACKGROUND: Pulmonary hypertension (PH) in COPD is a poorly investigated clinical condition.
• RESEARCH QUESTION: Which factors determine the outcome of PH in COPD?
• STUDY DESIGN AND METHODS: We analyzed the characteristics and outcome of patients enrolled in the Comparative, Prospective Registry of Newly Initiated Therapies for Pulmonary Hypertension (COMPERA) with moderate or severe PH in COPD as defined during the 6th PH World Symposium who received medical therapy for PH and compared them with patients with idiopathic pulmonary arterial hypertension (IPAH) .” 21
• EXAMPLE 4. Exploratory research question (qualitative research)
• - Explores areas that have not been fully investigated (perspectives of families and children who receive care in clinic-based child obesity treatment) to have a deeper understanding of the research problem
• “Problem: Interventions for children with obesity lead to only modest improvements in BMI and long-term outcomes, and data are limited on the perspectives of families of children with obesity in clinic-based treatment. This scoping review seeks to answer the question: What is known about the perspectives of families and children who receive care in clinic-based child obesity treatment? This review aims to explore the scope of perspectives reported by families of children with obesity who have received individualized outpatient clinic-based obesity treatment.” 22
• EXAMPLE 5. Relationship research question (quantitative research)
• - Defines interactions between dependent variable (use of ankle strategies) and independent variable (changes in muscle tone)
• “Background: To maintain an upright standing posture against external disturbances, the human body mainly employs two types of postural control strategies: “ankle strategy” and “hip strategy.” While it has been reported that the magnitude of the disturbance alters the use of postural control strategies, it has not been elucidated how the level of muscle tone, one of the crucial parameters of bodily function, determines the use of each strategy. We have previously confirmed using forward dynamics simulations of human musculoskeletal models that an increased muscle tone promotes the use of ankle strategies. The objective of the present study was to experimentally evaluate a hypothesis: an increased muscle tone promotes the use of ankle strategies. Research question: Do changes in the muscle tone affect the use of ankle strategies ?” 23

EXAMPLES OF HYPOTHESES IN PUBLISHED ARTICLES

• EXAMPLE 1. Working hypothesis (quantitative research)
• - A hypothesis that is initially accepted for further research to produce a feasible theory
• “As fever may have benefit in shortening the duration of viral illness, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response when taken during the early stages of COVID-19 illness .” 24
• “In conclusion, it is plausible to hypothesize that the antipyretic efficacy of ibuprofen may be hindering the benefits of a fever response . The difference in perceived safety of these agents in COVID-19 illness could be related to the more potent efficacy to reduce fever with ibuprofen compared to acetaminophen. Compelling data on the benefit of fever warrant further research and review to determine when to treat or withhold ibuprofen for early stage fever for COVID-19 and other related viral illnesses .” 24
• EXAMPLE 2. Exploratory hypothesis (qualitative research)
• - Explores particular areas deeper to clarify subjective experience and develop a formal hypothesis potentially testable in a future quantitative approach
• “We hypothesized that when thinking about a past experience of help-seeking, a self distancing prompt would cause increased help-seeking intentions and more favorable help-seeking outcome expectations .” 25
• “Conclusion
• Although a priori hypotheses were not supported, further research is warranted as results indicate the potential for using self-distancing approaches to increasing help-seeking among some people with depressive symptomatology.” 25
• EXAMPLE 3. Hypothesis-generating research to establish a framework for hypothesis testing (qualitative research)
• “We hypothesize that compassionate care is beneficial for patients (better outcomes), healthcare systems and payers (lower costs), and healthcare providers (lower burnout). ” 26
• Compassionomics is the branch of knowledge and scientific study of the effects of compassionate healthcare. Our main hypotheses are that compassionate healthcare is beneficial for (1) patients, by improving clinical outcomes, (2) healthcare systems and payers, by supporting financial sustainability, and (3) HCPs, by lowering burnout and promoting resilience and well-being. The purpose of this paper is to establish a scientific framework for testing the hypotheses above . If these hypotheses are confirmed through rigorous research, compassionomics will belong in the science of evidence-based medicine, with major implications for all healthcare domains.” 26
• EXAMPLE 4. Statistical hypothesis (quantitative research)
• - An assumption is made about the relationship among several population characteristics ( gender differences in sociodemographic and clinical characteristics of adults with ADHD ). Validity is tested by statistical experiment or analysis ( chi-square test, Students t-test, and logistic regression analysis)
• “Our research investigated gender differences in sociodemographic and clinical characteristics of adults with ADHD in a Japanese clinical sample. Due to unique Japanese cultural ideals and expectations of women's behavior that are in opposition to ADHD symptoms, we hypothesized that women with ADHD experience more difficulties and present more dysfunctions than men . We tested the following hypotheses: first, women with ADHD have more comorbidities than men with ADHD; second, women with ADHD experience more social hardships than men, such as having less full-time employment and being more likely to be divorced.” 27
• “Statistical Analysis
• ( text omitted ) Between-gender comparisons were made using the chi-squared test for categorical variables and Students t-test for continuous variables…( text omitted ). A logistic regression analysis was performed for employment status, marital status, and comorbidity to evaluate the independent effects of gender on these dependent variables.” 27

EXAMPLES OF HYPOTHESIS AS WRITTEN IN PUBLISHED ARTICLES IN RELATION TO OTHER PARTS

• EXAMPLE 1. Background, hypotheses, and aims are provided
• “Pregnant women need skilled care during pregnancy and childbirth, but that skilled care is often delayed in some countries …( text omitted ). The focused antenatal care (FANC) model of WHO recommends that nurses provide information or counseling to all pregnant women …( text omitted ). Job aids are visual support materials that provide the right kind of information using graphics and words in a simple and yet effective manner. When nurses are not highly trained or have many work details to attend to, these job aids can serve as a content reminder for the nurses and can be used for educating their patients (Jennings, Yebadokpo, Affo, & Agbogbe, 2010) ( text omitted ). Importantly, additional evidence is needed to confirm how job aids can further improve the quality of ANC counseling by health workers in maternal care …( text omitted )” 28
• “ This has led us to hypothesize that the quality of ANC counseling would be better if supported by job aids. Consequently, a better quality of ANC counseling is expected to produce higher levels of awareness concerning the danger signs of pregnancy and a more favorable impression of the caring behavior of nurses .” 28
• “This study aimed to examine the differences in the responses of pregnant women to a job aid-supported intervention during ANC visit in terms of 1) their understanding of the danger signs of pregnancy and 2) their impression of the caring behaviors of nurses to pregnant women in rural Tanzania.” 28
• EXAMPLE 2. Background, hypotheses, and aims are provided
• “We conducted a two-arm randomized controlled trial (RCT) to evaluate and compare changes in salivary cortisol and oxytocin levels of first-time pregnant women between experimental and control groups. The women in the experimental group touched and held an infant for 30 min (experimental intervention protocol), whereas those in the control group watched a DVD movie of an infant (control intervention protocol). The primary outcome was salivary cortisol level and the secondary outcome was salivary oxytocin level.” 29
• “ We hypothesize that at 30 min after touching and holding an infant, the salivary cortisol level will significantly decrease and the salivary oxytocin level will increase in the experimental group compared with the control group .” 29
• EXAMPLE 3. Background, aim, and hypothesis are provided
• “In countries where the maternal mortality ratio remains high, antenatal education to increase Birth Preparedness and Complication Readiness (BPCR) is considered one of the top priorities [1]. BPCR includes birth plans during the antenatal period, such as the birthplace, birth attendant, transportation, health facility for complications, expenses, and birth materials, as well as family coordination to achieve such birth plans. In Tanzania, although increasing, only about half of all pregnant women attend an antenatal clinic more than four times [4]. Moreover, the information provided during antenatal care (ANC) is insufficient. In the resource-poor settings, antenatal group education is a potential approach because of the limited time for individual counseling at antenatal clinics.” 30
• “This study aimed to evaluate an antenatal group education program among pregnant women and their families with respect to birth-preparedness and maternal and infant outcomes in rural villages of Tanzania.” 30
• “ The study hypothesis was if Tanzanian pregnant women and their families received a family-oriented antenatal group education, they would (1) have a higher level of BPCR, (2) attend antenatal clinic four or more times, (3) give birth in a health facility, (4) have less complications of women at birth, and (5) have less complications and deaths of infants than those who did not receive the education .” 30

Research questions and hypotheses are crucial components to any type of research, whether quantitative or qualitative. These questions should be developed at the very beginning of the study. Excellent research questions lead to superior hypotheses, which, like a compass, set the direction of research, and can often determine the successful conduct of the study. Many research studies have floundered because the development of research questions and subsequent hypotheses was not given the thought and meticulous attention needed. The development of research questions and hypotheses is an iterative process based on extensive knowledge of the literature and insightful grasp of the knowledge gap. Focused, concise, and specific research questions provide a strong foundation for constructing hypotheses which serve as formal predictions about the research outcomes. Research questions and hypotheses are crucial elements of research that should not be overlooked. They should be carefully thought of and constructed when planning research. This avoids unethical studies and poor outcomes by defining well-founded objectives that determine the design, course, and outcome of the study.

Disclosure: The authors have no potential conflicts of interest to disclose.

Author Contributions:

• Conceptualization: Barroga E, Matanguihan GJ.
• Methodology: Barroga E, Matanguihan GJ.
• Writing - original draft: Barroga E, Matanguihan GJ.
• Writing - review & editing: Barroga E, Matanguihan GJ.