Research Hypothesis – Types, Examples Characteristics, and Sources

Research hypothesis.

A research hypothesis is referred to as a scientific hypothesis. This is a clear, specific, and testable statement that predicts the expected result in a scientific study. It is a prediction, reasonable guess, and logical supposition about the relationship between the variables. A research hypothesis is an integral and central part of research whether it is exploratory or explanatory, qualitative or quantitative. It creates the base of scientific experiments. So, you must be very careful while building any hypothesis.

A hypothesis can be correct or wrong. It is tested through experiments or research to determine whether it is correct or incorrect.

Functions of research  hypothesis

There are major functions of research hypothesis that are as follow:

Sources of hypothesis

Following are the sources of the hypothesis:

Characteristics of an effective research hypothesis

Following are the characteristics of an effective research hypothesis:

Types of research hypothesis

Following are the types of research hypotheses.

It shows a relationship between a single dependent variable and an independent variable. For instance, if you take in more carbs and fats, you will gain obesity. Here taking more carbs and fats are an independent variable and gaining weight is the dependent variable.

It predicts the relationship between two or more independent variables and dependent variables. For example, we can say that taking in more carbs and fats can cause obesity along with other problems like high blood pressure, heart disease, and so on.

Typically, directional hypotheses are derived from theory. This type of hypothesis shows the researcher’s intellectual commitment towards a specific outcome. The researcher predicts the existence and nature of a relationship between variables.

The non-directional hypothesis is used when there is no theory and the findings of studies are contradictory.  It shows the relationship between two variables but does not set down the expected direction or nature of the relationship.

Null hypotheses are made when there is no empirical and adequate theoretical information to show a hypothesis. The null hypothesis negates the relationship between variables. It is denoted by Ho. This hypothesis is made when the researcher wants to reject or disapprove the null hypothesis. It is contrary to what an experimenter or investigator expects. The purpose is to confirm the existence of a relationship between the variables.

The null hypothesis can be:

1. Alternative hypothesis

When a hypothesis is rejected, then another hypothesis is made to be tested and show the desired results. This is called an alternative hypothesis. It is opposite to the null hypothesis and is made to disprove that hypothesis. This hypothesis is denoted by H1.

2. Statistical hypothesis

As the name mentions, this hypothesis has the quality to be verified statistically. It is tested by using quantitative techniques. The variables in this hypothesis are quantifiable and can also transform into quantifiable indicators to verify it statistically.

This hypothesis is used when a theory is tested with observation and experiment. It is just a notion or idea. This hypothesis goes through trial and error by changing independent variables. The series of trial and error helps to find the best result. The outcomes of these experiments can be proven over time.

The associative hypothesis shows interdependency between variables. Any change in one variable causes the change in another variable. Whereas, the causal hypothesis shows a cause and effect between variables.

How to formulate a research hypothesis

There are some important points you must consider while formulating a hypothesis:

The first and foremost thing for creating a research hypothesis is to generate a research question. The question should be specific, focused, and researchable within the limitations of your project.

Now try to find the answer to your question. The initial answer must be based on previous knowledge about the topic. Concern theories and previous studies and try to form assumptions about what you will find in your research.

Create a conceptual framework about different variables you are going to study and the relationships between them.

Now you have an idea of what you are expecting to find. Make a clear and concise answer to the question.

Now check whether your hypothesis is testable. There must be clear definitions of your hypothesis while phrasing. It should contain:

The particular group being studied.

The predicted result of the analysis or experiment

To recognize the variables, write a prediction in (if-then) form. Like, if a particular action is taken, a certain result is expected. The first part of the phrase shows the independent variable while the second part shows the dependent variable.

If the research requires statistical hypothesis testing, you must have to make a null hypothesis and an alternative hypothesis.

Now test your hypothesis through observations, techniques, and experiments by keeping necessary things and resources in consideration.

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Just-world hypothesis, what is the just-world hypothesis.

The  just-world hypothesis  refers to our belief that the world is fair, and consequently, that the moral standings of our actions will determine our outcomes. This viewpoint causes us to believe that those who do good will be rewarded, and those who exhibit negative behaviors will be punished.

Where it occurs

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Imagine that it is a Friday evening and you and your friends are leaving your favorite restaurant. Spirits are high as you walk back to the side street where you parked your cars. Your friend Paul’s lively demeanor quickly changes as his car comes into view with the passenger door wide open. He runs to assess the damage, finding that his car radio and laptop have been stolen. You console Paul and ask how this could have happened, and he says he has no idea. You continue to comfort your friend, but you can’t help but feel that he must have left his doors unlocked and laptop in plain sight. You start to think about how Paul is always so absent-minded and maybe needed a bit of a wake-up call.

Here we can see how the just-world hypothesis can shape our perception. You assume that what goes around comes around, and thus, rationalize Paul’s misfortune as a consequence of his negative actions or characteristics. You even distort your perception of Paul to find a reason that he was robbed instead of you.

Related Biases

Individual effects

On an individual level, there are ups and downs to the just-world hypothesis (also referred to as  the just-world bias  or  just-world fallacy ). Belief in a just world can motivate us to act with morality and integrity, which is commonly thought of as ‘keeping good karma’. However, the world is not always as righteous as we would hope. By holding tightly to the just-world hypothesis in the face of injustice, we are susceptible to making inaccurate conclusions and judgments about the world around us. UCLA social psychologists Zick Rubin and Letitia Ann Peplau aptly state, “People often exert tremendous effort in order to help right social wrongs and thus help restore justice in the world. At other times, however, people’s desire to live in a just world leads not to justice but to  justification”. 1  The firm belief in a just world yields a cognitive bias and can result in us justifying a person’s suffering through painting them negatively or minimizing their suffering altogether.

Let’s look at how this could apply in our everyday lives. For example, we might look at someone with a low-paying job and assume they are less hard-working than someone deemed more successful. Our judgments may ignore socioeconomic barriers that this person may face, as well as the long, hard hours they may work. We create these false narratives to protect our world theory. We want to believe that the world is fair and if you work hard you will get ahead, It can be easier to label someone as lazy or unmotivated rather than admit that the world can be unfair.

We can see in this example how this outlook is also driven by the  fundamental attribution error , which refers to our tendency to focus on people’s traits rather than situational factors. This causes us to assume that those who deserve success will achieve it, but forget that the playing field is not always even.

Systemic effects

The way we decide what deserves punishment and what merits reward dictates how we see the world. This outlook, shared by most people to varying degrees, has significant effects on political and legal outcomes. Individual variances in the cognitive strength of the just-world hypothesis (how much we believe that the world is truly just) and response to apparent injustices (i.e. rationalizing, ignoring, or intervening) are echoed in political opinions, especially regarding attitudes towards political leaders, attitudes towards victims, and attitudes towards social activism. Research by Rubin and Pelau showed an inverse correlation between the just-world hypothesis and social activism. 1  If you believe the world is fair as it is, you will be less likely to take action and fight for change.

Why it happens

We are socialized to believe that good is always rewarded and evil is punished. From early childhood, we read stories of courageous heroes saving the day and being rewarded with keys to the city, while villains are slain or banished. In these stories, the characters always reap what they sow. Rubin and Peplau cite research in childhood development, stating that we develop this sense of justice expected to be inherent in the world relatively early on. 2

As humans, we are often faced with an overwhelming amount of information. To make sense of our surroundings, we construct cognitive frameworks to guide our decision-making and predict outcomes. The just-world hypothesis serves as one of these frameworks, creating an understanding of positive and negative occurrences by attributing them to a larger karmic cycle.

Belief in a just world creates a seemingly predictable environment

Social psychologist and pioneer of just world research, Dr. Melvin J Lerner, describes how the just-world hypothesis installs an image of a “manageable and predictable world [which are] central to the ability to engage in long-term goal-directed activity”. 3   Basically, we are more likely to work towards our goals if we feel like we can predict the result. Also, studies have shown that viewing the world as predictable and fair also protects people from helplessness, which is detrimental to human psychological and physical well-being.  4

We often avoid or distort information that challenges our cognitive framework

When we feel physically uncomfortable, it is almost second nature to do whatever it takes to put ourselves at ease. This happens mentally too. We can all probably relate to the feeling of discomfort when our beliefs are challenged or we are proved wrong. Sometimes this can cause us to get defensive or find ways to invalidate opposing information. Social psychologist Leon Festinger coined this phenomenon as  cognitive dissonance , stating that, “ if a person knows various things that are not psychologically consistent with one another, he will, in a variety of ways, try to make them more consistent”  5 . The just-world hypothesis causes mental distortions in order to cope with the apparent inconsistencies of the world.

Why it is important

How strongly the just-world hypothesis manifests in us can truly shape our entire understanding of the world. It changes our perception of others. It creates certain expectations for ourselves. The desire for justice is not the same as the belief that the world is just. To create social change, we must have the clarity to see where a situation may be unfair or take the time to truly understand someone’s circumstances before casting judgment. The just-world hypothesis can create harmful and delusional modes of thinking with serious consequences socially, politically, and legally.

How to avoid it

Lauded behavioral scientists Daniel Kahneman and Amos Tversky propose two disparate modes of thinking 6 . System 1 refers to our knee-jerk responses, our quickly-made judgments, our emotional reactions. System 2 refers to a slower, more rational, more calculated thinking process. Many of our biases are elicited through System 1 thinking, including the just-world hypothesis.

By understanding the two systems of thinking, we are better equipped to resist biases

Understanding the dual-processing mode of thinking can help us consciously hone in on the more analytic, System 2 type of thinking. A survey of various debiasing techniques found that they all shared a common thread of deliberately moving from System 1 thinking to System 2. 7  Slowing down the process by which we make our judgments and considering all of the information at hand allows us to make better decisions.

With the just-world hypothesis, System 2 thinking means taking a step back to prevent ourselves from making distorted assessments. Sometimes after looking at the full picture we will still support our initial conclusion. Maybe we still feel that the punishment or reward at hand was warranted, and that is okay too. Working on de-biasing the just-world hypothesis does not mean telling ourselves that the world is  never just.  What we want to open our minds to is a new way of dealing with cognitive dissonance instead of always taking the easiest route. By simply using System 2 thinking, we can think critically, rather than instinctually. This will allow us to clearly see injustices and better prepare ourselves and the world around us to combat them.

So how do we slow down and start using System 2 thinking? Well, the answer to this is less clear-cut. Just like when we are learning a new physical skill, building positive mental practices takes time and repetition. We now know what the just-world hypothesis is and how it happens, so we can be more aware of it in ourselves. At first, we might retroactively realize when we are thinking in a biased manner, per se making a quick judgment about someone. Through examining our intuitive judgments and looking at the larger picture, we can cultivate proactive System 2 thinking.

We can fight victim-blaming tendencies by cultivating empathy

One tool we can use to combat the negative attitudes towards victims sometimes unknowingly yielded by the just-world hypothesis is empathy. In one experiment led by researchers Aderman, Brehm, and Katz from Duke University, participants were asked to watch a video of a woman receiving electric shocks based on her performance in a learning task.  8  Before watching this tape, participants were either asked to imagine themselves in the scenario or just asked to simply watch the woman in the tape. Those who were in the empathy-inducing group were much less likely to derogate the victim, demonstrating less influence of the just-world hypothesis. So, if we can remember to think critically rather than instinctually, and put ourselves in the shoes of others, we can more accurately assess the situation.

How it all started

Dr. Melvin J Lerner was the first to explicitly define and research the just-world hypothesis. Lerner was doing his postdoctoral work in clinical psychology at a major mental institution when he discovered an interest in the phenomena.  9  He worked alongside psychologists and therapists as they cared for patients and assessed if the patients were ready to be reintegrated into society. Yet, he noticed an unsettling pattern in the attitudes of the workers towards their patients. He saw these medical professionals relentlessly cross-examining patients in therapy sessions, which caused emotional distress, and he would hear them talking about patients in an incredibly derogatory manner.

After watching these strange behaviors elicited by otherwise compassionate and intelligent people, Lerner came to an interesting conclusion. Lerner found that the psychologists and therapists’ demeaning attitude towards patients functioned as a defense mechanism against feeling the patients were helpless. It also allowed them to cope with the patients’ suffering. From these observations and additional experimental research, Lerner formulated the just-world hypothesis as a way of “making sense of how people make sense of the world”.

Example 1 - Reactions to luck

In one study by Rubin and Peplau, participants’ responses to drawings of the National Draft Lottery for the Vietnam War were recorded and analyzed.  10  Groups of drafted men were asked to listen to the live broadcast in which their lottery numbers were assigned either high priority or low priority. Those with high priority lottery numbers were more likely to be inducted and face a more dangerous fate than those with low priority numbers. The drawings were entirely random, thus, no predetermining factors indicated the mens’ outcomes.

They found that for the most part participants acted with sympathy towards those with a high priority drawing. However, the results differed in those who scored highly for the just-world hypothesis. These participants had more resentment for the losers (those who received a high priority number and were more likely to be sent into war), even though the losers were  entirely victims of circumstance . The researchers suggested that this resentment was yielded by the need to “justify an underlying moral order”.

Example 2 - Perceptions of leaders

In a 1973 study at UCLA, Peplau investigated how the just-world hypothesis influenced political attitudes.  11  They found that high scores in belief in a just world indicated higher approval ratings for major political institutions, such as the “US Congress, Supreme Court, military, big business, and labor unions”.

Incidentally, this study took place during the Watergate Scandal, where the Nixon administration was accused of organizing a break-in to the Democratic National Committee office. The researchers ended up finding that participants scoring highly on a measure for strength of the just-world hypothesis were  less likely  to believe that President Nixon was guilty. These participants associated such high levels of success with a strong character and moral compass, thus, they did not believe that Nixon was capable of such deceptive acts.

The just-world hypothesis refers to the belief that the world is fair and how morally we act will determine our outcomes. With the just-world hypothesis comes a tendency to rationalize information around us to fit this belief.

For us, a just world is a predictable world; we expect a reward when we work hard and we expect punishment for wrongdoings. The just-world hypothesis is a lens for understanding the world around us that provides stability. So when we are faced with a situation that seems unjust, this results in  cognitive dissonance  between our beliefs about the world and reality. We mitigate this dissonance by finding ways to justify the injustice.

Example 1 –  How the just-world hypothesis changes our reaction to situations of luck

In a study done on the drawing of priority numbers for men drafted into the Vietnam War, men with high scores for the just-world hypothesis were  more likely to have negative feelings  towards those who had a higher chance of being sent to war.

Example 2 – How the just-world hypothesis can skew our perception of leaders

Those who have a strong belief in a just world may have higher approval for political leaders due to the assumption that you achieve success through high merit and moral strength. In a study surveying political attitudes during the Watergate Scandal, the participants with high scores for the just-world hypothesis were more likely to  deny  Nixon’s guilt.

We can learn to avoid judgments clouded by the just-world hypothesis by moving from System 1 thinking (quickly made, intuitive responses) to System 2 (slower, analytical processing). Additionally, we can visualize ourselves in someone else’s position to encourage empathy and prevent victim-blaming.

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The null hypothesis refers to the ______, whereas the research hypothesis refers to the ______.

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Introduction to Research Methods in Psychology

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

research hypothesis refer to

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity,, GoodTherapy, Vox, and Verywell.

research hypothesis refer to

There are several different research methods in psychology , each of which can help researchers learn more about the way people think, feel, and behave. If you're a psychology student or just want to know the types of research in psychology, here are the main ones as well as how they work.

Three Main Types of Research in Psychology

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Psychology research can usually be classified as one of three major types.

1. Causal or Experimental Research

When most people think of scientific experimentation, research on cause and effect is most often brought to mind. Experiments on causal relationships investigate the effect of one or more variables on one or more outcome variables. This type of research also determines if one variable causes another variable to occur or change.

An example of this type of research in psychology would be changing the length of a specific mental health treatment and measuring the effect on study participants.

2. Descriptive Research

Descriptive research seeks to depict what already exists in a group or population. Three types of psychology research utilizing this method are:

An example of this psychology research method would be an opinion poll to determine which presidential candidate people plan to vote for in the next election. Descriptive studies don't try to measure the effect of a variable; they seek only to describe it.

3. Relational or Correlational Research

A study that investigates the connection between two or more variables is considered relational research. The variables compared are generally already present in the group or population.

For example, a study that looks at the proportion of males and females that would purchase either a classical CD or a jazz CD would be studying the relationship between gender and music preference.

Theory vs. Hypothesis in Psychology Research

People often confuse the terms theory and hypothesis or are not quite sure of the distinctions between the two concepts. If you're a psychology student, it's essential to understand what each term means, how they differ, and how they're used in psychology research.

A theory is a well-established principle that has been developed to explain some aspect of the natural world. A theory arises from repeated observation and testing and incorporates facts, laws, predictions, and tested hypotheses that are widely accepted.

A hypothesis is a specific, testable prediction about what you expect to happen in your study. For example, an experiment designed to look at the relationship between study habits and test anxiety might have a hypothesis that states, "We predict that students with better study habits will suffer less test anxiety." Unless your study is exploratory in nature, your hypothesis should always explain what you expect to happen during the course of your experiment or research.

While the terms are sometimes used interchangeably in everyday use, the difference between a theory and a hypothesis is important when studying experimental design.

Some other important distinctions to note include:

The Effect of Time on Research Methods in Psychology

There are two types of time dimensions that can be used in designing a research study:

The effects of aging are often investigated using longitudinal research.

Causal Relationships Between Psychology Research Variables

What do we mean when we talk about a “relationship” between variables? In psychological research, we're referring to a connection between two or more factors that we can measure or systematically vary.

One of the most important distinctions to make when discussing the relationship between variables is the meaning of causation.

A causal relationship is when one variable causes a change in another variable. These types of relationships are investigated by experimental research to determine if changes in one variable actually result in changes in another variable.

Correlational Relationships Between Psychology Research Variables

A correlation is the measurement of the relationship between two variables. These variables already occur in the group or population and are not controlled by the experimenter.

In both types of correlation, there is no evidence or proof that changes in one variable cause changes in the other variable. A correlation simply indicates that there is a relationship between the two variables.

The most important concept is that correlation does not equal causation. Many popular media sources make the mistake of assuming that simply because two variables are related, a causal relationship exists.

Psychologists use descriptive, correlational, and experimental research designs to understand behavior . In:  Introduction to Psychology . Minneapolis, MN: University of Minnesota Libraries Publishing; 2010.

Caruana EJ, Roman M, Herandez-Sanchez J, Solli P. Longitudinal studies . Journal of Thoracic Disease. 2015;7(11):E537-E540. doi:10.3978/j.issn.2072-1439.2015.10.63

University of Berkeley. Science at multiple levels . Understanding Science 101 . Published 2012.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

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An hypothesis is a specific statement of prediction. It describes in concrete (rather than theoretical) terms what you expect will happen in your study. Not all studies have hypotheses. Sometimes a study is designed to be exploratory (see inductive research ). There is no formal hypothesis, and perhaps the purpose of the study is to explore some area more thoroughly in order to develop some specific hypothesis or prediction that can be tested in future research. A single study may have one or many hypotheses.

Actually, whenever I talk about an hypothesis, I am really thinking simultaneously about two hypotheses. Let’s say that you predict that there will be a relationship between two variables in your study. The way we would formally set up the hypothesis test is to formulate two hypothesis statements, one that describes your prediction and one that describes all the other possible outcomes with respect to the hypothesized relationship. Your prediction is that variable A and variable B will be related (you don’t care whether it’s a positive or negative relationship). Then the only other possible outcome would be that variable A and variable B are not related. Usually, we call the hypothesis that you support (your prediction) the alternative hypothesis, and we call the hypothesis that describes the remaining possible outcomes the null hypothesis. Sometimes we use a notation like HA or H1 to represent the alternative hypothesis or your prediction, and HO or H0 to represent the null case. You have to be careful here, though. In some studies, your prediction might very well be that there will be no difference or change. In this case, you are essentially trying to find support for the null hypothesis and you are opposed to the alternative.

If your prediction specifies a direction, and the null therefore is the no difference prediction and the prediction of the opposite direction, we call this a one-tailed hypothesis . For instance, let’s imagine that you are investigating the effects of a new employee training program and that you believe one of the outcomes will be that there will be less employee absenteeism. Your two hypotheses might be stated something like this:

The null hypothesis for this study is:

HO: As a result of the XYZ company employee training program, there will either be no significant difference in employee absenteeism or there will be a significant increase .

which is tested against the alternative hypothesis:

HA: As a result of the XYZ company employee training program, there will be a significant decrease in employee absenteeism.

In the figure on the left, we see this situation illustrated graphically. The alternative hypothesis – your prediction that the program will decrease absenteeism – is shown there. The null must account for the other two possible conditions: no difference, or an increase in absenteeism. The figure shows a hypothetical distribution of absenteeism differences. We can see that the term “one-tailed” refers to the tail of the distribution on the outcome variable.

When your prediction does not specify a direction, we say you have a two-tailed hypothesis . For instance, let’s assume you are studying a new drug treatment for depression. The drug has gone through some initial animal trials, but has not yet been tested on humans. You believe (based on theory and the previous research) that the drug will have an effect, but you are not confident enough to hypothesize a direction and say the drug will reduce depression (after all, you’ve seen more than enough promising drug treatments come along that eventually were shown to have severe side effects that actually worsened symptoms). In this case, you might state the two hypotheses like this:

HO: As a result of 300mg./day of the ABC drug, there will be no significant difference in depression.
HA: As a result of 300mg./day of the ABC drug, there will be a significant difference in depression.

The figure on the right illustrates this two-tailed prediction for this case. Again, notice that the term “two-tailed” refers to the tails of the distribution for your outcome variable.

The important thing to remember about stating hypotheses is that you formulate your prediction (directional or not), and then you formulate a second hypothesis that is mutually exclusive of the first and incorporates all possible alternative outcomes for that case. When your study analysis is completed, the idea is that you will have to choose between the two hypotheses. If your prediction was correct, then you would (usually) reject the null hypothesis and accept the alternative. If your original prediction was not supported in the data, then you will accept the null hypothesis and reject the alternative. The logic of hypothesis testing is based on these two basic principles:

OK, I know it’s a convoluted, awkward and formalistic way to ask research questions. But it encompasses a long tradition in statistics called the hypothetical-deductive model , and sometimes we just have to do things because they’re traditions. And anyway, if all of this hypothesis testing was easy enough so anybody could understand it, how do you think statisticians would stay employed?

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