Research Hypothesis: Definition, Types, & Examples
Saul Mcleod, PhD
BSc (Hons) Psychology, MRes, PhD, University of Manchester
Saul Mcleod, Ph.D., is a qualified psychology teacher with over 18 years experience of working in further and higher education.
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Associate Editor for Simply Psychology
BSc (Hons), Psychology, MSc, Psychology of Education
Olivia Guy-Evans is a writer and associate editor for Simply Psychology. She has previously worked in healthcare and educational sectors.
A hypothesis (plural hypotheses) is a precise, testable statement of what the researcher(s) predict will be the outcome of the study. It is stated at the start of the study.
This usually involves proposing a possible relationship between two variables: the independent variable (what the researcher changes) and the dependent variable (what the research measures).
In research, there is a convention that the hypothesis is written in two forms, the null hypothesis, and the alternative hypothesis (called the experimental hypothesis when the method of investigation is an experiment ).
A fundamental requirement of a hypothesis is that is can be tested against reality, and can then be supported or rejected.
To test a hypothesis the researcher first assumes that there is no difference between populations from which they are taken. This is known as the null hypothesis. The research hypothesis is often called the alternative hypothesis.
In This Article
Types of research hypotheses
The alternative hypothesis states that there is a relationship between the two variables being studied (one variable has an effect on the other).
An experimental hypothesis predicts what change(s) will take place in the dependent variable when the independent variable is manipulated.
It states that the results are not due to chance and that they are significant in terms of supporting the theory being investigated.
The null hypothesis states that there is no relationship between the two variables being studied (one variable does not affect the other). There will be no changes in the dependent variable due to the manipulation of the independent variable.
It states results are due to chance and are not significant in terms of supporting the idea being investigated.
A non-directional (two-tailed) hypothesis predicts that the independent variable will have an effect on the dependent variable, but the direction of the effect is not specified. It just states that there will be a difference.
E.g., there will be a difference in how many numbers are correctly recalled by children and adults.
A directional (one-tailed) hypothesis predicts the nature of the effect of the independent variable on the dependent variable. It predicts in which direction the change will take place. (i.e. greater, smaller, less, more)
E.g., adults will correctly recall more words than children.
The Falsification Principle, proposed by Karl Popper , is a way of demarcating science from non-science. It suggests that for a theory to be considered scientific it must be able to be tested and conceivably proven false.
However many confirming instances there are for a theory, it only takes one counter observation to falsify it. For example, the hypothesis that “all swans are white,” can be falsified by observing a black swan.
For Popper, science should attempt to disprove a theory, rather than attempt to continually support theoretical hypotheses.
Can a hypothesis be proven?
Upon analysis of the results, an alternative hypothesis can be rejected or supported, but it can never be proven to be correct. We must avoid any reference to results proving a theory as this implies 100% certainty, and there is always a chance that evidence may exist which could refute a theory.
How to write a hypothesis
- 1. To write the alternative and null hypotheses for an investigation, you need to identify the key variables in the study.The independent variable is manipulated by the researcher and the dependent variable is the outcome which is measured.
- 2. Operationalized the variables being investigated.Operationalisation of a hypothesis refers to the process of making the variables physically measurable or testable, e.g. if you are about to study aggression you might count the number of punches given by participants
- 3. Decide on a direction for your prediction. If there is evidence in the literature to support a specific effect on the independent variable on the dependent variable, write a directional (one-tailed) hypothesis.If there are limited or ambiguous findings in the literature regarding the effect of the independent variable on the dependent variable, write a non-directional (two-tailed) hypothesis.
- 4. Write your hypothesis. A good hypothesis is short (i.e. concise) and comprises clear and simple language.
What are examples of a hypothesis?
Let’s consider a hypothesis that many teachers might subscribe to: that students work better on Monday morning than they do on a Friday afternoon (IV=Day, DV=Standard of work).
Now, if we decide to study this by giving the same group of students a lesson on a Monday morning and on a Friday afternoon and then measuring their immediate recall on the material covered in each session we would end up with the following:
- The alternative hypothesis states that students will recall significantly more information on a Monday morning than on a Friday afternoon.
- The null hypothesis states that there will be no significant difference in the amount recalled on a Monday morning compared to a Friday afternoon. Any difference will be due to chance or confounding factors.
The null hypothesis is, therefore, the opposite of the alternative hypothesis in that it states that there will be no change in behavior.
At this point, you might be asking why we seem so interested in the null hypothesis. Surely the alternative (or experimental) hypothesis is more important?
Well, yes it is. However, we can never 100% prove the alternative hypothesis. What we do instead is see if we can disprove, or reject, the null hypothesis.
If we reject the null hypothesis, this doesn’t really mean that our alternative hypothesis is correct – but it does provide support for the alternative / experimental hypothesis.
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What is the difference between a one-tailed hypothesis and a two-tailed hypothesis?
Both one-tailed and two-tailed hypothesis are examples of alternative or experimental hypothesis, which predict there will be a psychological effect. A one tailed hypothesis, also known as a directional hypothesis, points to what direction the effect will appear in, for example if we were studying whether student's attendance affects their grades, the one tailed hypothesis would be that students with higher attendance will have significantly higher grades than students with low attendance. On the other hand, a two-tailed hypothesis, also known as non-directional, will still predict that there will be an effect, but will not say what direction it will appear in. For example, in the same study a two-tailed hypothesis might look like, there will be a significant difference in the grades of students with high attendance and students with low attendance.A null hypothesis is separate as it says that there will not be a psychological test in either condition.
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Two-tailed or one-tailed test?
Travis Dixon April 13, 2021 Internal Assessment (IB)
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Everything you need for the IA in an instant download. Available here .
I can almost guarantee you’ll need a one-tailed test for your inferential statistics in the IB Psychology IA. Let’s see why.
It’s one of the most common mistakes made in the analysis, but it’s so easy to avoid. Do you need a one or two-tailed inferential statistics test (e.g. MWU or Wilcoxon)?
The Easy Answer
- If you have a one-tailed hypothesis, you must do a one-tailed inferential test.
- If you have a two-tailed hypothesis, you must do a two-tailed test.
Many students do a two-tailed test for a one-tailed hypothesis. If you do this it limits the maximum marks you can score in the analysis to 4/6. Even if you do everything else perfect but you make this one little mistake, you lose two marks.
The one vs two tailed debate still continues in Psychology ( read more ). The IB ignores this and makes it simple: one tailed hypotheses = one tailed test. No ifs, ands, or buts!
- Blog: Hypotheses – How to write hypotheses
- Blog: Lesson Idea: Inferential Statistics
- Video: How to do the Mann Whitney U test online
- Video: Internal Assessment Playlist
One vs two-tailed hypothesis: What’s the difference?
If you are predicting that one of your conditions in your experiment will have a higher value than the other, it’s one-tailed (because you know the direction of the effect – the IV is increasing the DV). Similarly, your hypothesis is one-tailed if you are predicting that manipulating the IV will cause a decrease in the DV.
However, if you think your IV will have an effect, but you’re not sure if it will increase or decrease it, this is two-tailed. You can see some example hypotheses here .
The default on the SocSci MWU calculator is two-tailed. Be sure to change it if you have a one-tailed hypothesis.
I’m almost 99% certain your hypothesis is one-tailed, but please double-check (and if it’s two-tailed leave a comment). The reason it’s probably one-tailed is because you have to be able to link your investigation to a theory. This invariably means explaining the results of an original study using a background theory. If you can use a theory to explain the results you know what direction to expect the results of your study.
The best online calculator?
The two most popular choices are VassarStats and Socscistatistics. I prefer https://www.socscistatistics.com/ because they provide a more clear summary of results which I find easier to interpret. For example, for the MWU test vassarstats provides two p values and two U values. The interface and reports are more confusing for vassarstats, I find.
Doing well on the IB Psych IA is about paying attention to detail. If you got this far in this post, I think you’re on track to do just great!
Travis Dixon is an IB Psychology teacher, author, workshop leader, examiner and IA moderator.
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Hypotheses; directional and non-directional, what is the difference between an experimental and an alternative hypothesis.
Nothing much! If the study is a laboratory experiment then we can call the hypothesis “an experimental hypothesis”, where we make a prediction about how the IV causes an effect on the DV. If we have a non-experimental design, i.e. we are not able to manipulate the IV as in a natural or quasi-experiment , or if some other research method has been used, then we call it an “alternativehypothesis”, alternative to the null.
Directional hypothesis: A directional (or one tailed hypothesis) states which way you think the results are going to go, for example in an experimental study we might say…”Participants who have been deprived of sleep for 24 hours will have more cold symptoms in the following week after exposure to a virus than participants who have not been sleep deprived”; the hypothesis compares the two groups/conditions and states which one will ….have more/less, be quicker/slower, etc.
If we had a correlational study, the directional hypothesis would state whether we expect a positive or a negative correlation, we are stating how the two variables will be related to each other, e.g. there will be a positive correlation between the number of stressful life events experienced in the last year and the number of coughs and colds suffered, whereby the more life events you have suffered the more coughs and cold you will have had”. The directional hypothesis can also state a negative correlation, e.g. the higher the number of face-book friends, the lower the life satisfaction score “
Non-directional hypothesis: A non-directional (or two tailed hypothesis) simply states that there will be a difference between the two groups/conditions but does not say which will be greater/smaller, quicker/slower etc. Using our example above we would say “There will be a difference between the number of cold symptoms experienced in the following week after exposure to a virus for those participants who have been sleep deprived for 24 hours compared with those who have not been sleep deprived for 24 hours.”
When the study is correlational, we simply state that variables will be correlated but do not state whether the relationship will be positive or negative, e.g. there will be a significant correlation between variable A and variable B.
Null hypothesis The null hypothesis states that the alternative or experimental hypothesis is NOT the case, if your experimental hypothesis was directional you would say…
Participants who have been deprived of sleep for 24 hours will NOT have more cold symptoms in the following week after exposure to a virus than participants who have not been sleep deprived and any difference that does arise will be due to chance alone.
or with a directional correlational hypothesis….
There will NOT be a positive correlation between the number of stress life events experienced in the last year and the number of coughs and colds suffered, whereby the more life events you have suffered the more coughs and cold you will have had”
With a non-directional or two tailed hypothesis…
There will be NO difference between the number of cold symptoms experienced in the following week after exposure to a virus for those participants who have been sleep deprived for 24 hours compared with those who have not been sleep deprived for 24 hours.
or for a correlational …
there will be NO correlation between variable A and variable B.
When it comes to conducting an inferential stats test, if you have a directional hypothesis , you must do a one tailed test to find out whether your observed value is significant. If you have a non-directional hypothesis , you must do a two tailed test .
- Remember, a decent hypothesis will contain two variables, in the case of an experimental hypothesis there will be an IV and a DV; in a correlational hypothesis there will be two co-variables
- both variables need to be fully operationalised to score the marks, that is you need to be very clear and specific about what you mean by your IV and your DV; if someone wanted to repeat your study, they should be able to look at your hypothesis and know exactly what to change between the two groups/conditions and exactly what to measure (including any units/explanation of rating scales etc, e.g. “where 1 is low and 7 is high”)
- double check the question, did it ask for a directional or non-directional hypothesis?
- if you were asked for a null hypothesis, make sure you always include the phrase “and any difference/correlation (is your study experimental or correlational?) that does arise will be due to chance alone”
- Mr Faraz wants to compare the levels of attendance between his psychology group and those of Mr Simon, who teaches a different psychology group. Which of the following is a suitable directional (one tailed) hypothesis for Mr Faraz’s investigation?
A There will be a difference in the levels of attendance between the two psychology groups.
B Students’ level of attendance will be higher in Mr Faraz’s group than Mr Simon’s group.
C Any difference in the levels of attendance between the two psychology groups is due to chance.
D The level of attendance of the students will depend upon who is teaching the groups.
2. Tracy works for the local council. The council is thinking about reducing the number of people it employs to pick up litter from the street. Tracy has been asked to carry out a study to see if having the streets cleaned at less regular intervals will affect the amount of litter the public will drop. She studies a street to compare how much litter is dropped at two different times, once when it has just been cleaned and once after it has not been cleaned for a month.
Write a fully operationalised non-directional (two-tailed) hypothesis for Tracy’s study. (2)
3. Jamila is conducting a practical investigation to look at gender differences in carrying out visuo-spatial tasks. She decides to give males and females a jigsaw puzzle and will time them to see who completes it the fastest. She uses a random sample of pupils from a local school to get her participants.
(a) Write a fully operationalised directional (one tailed) hypothesis for Jamila’s study. (2) (b) Outline one strength and one weakness of the random sampling method. You may refer to Jamila’s use of this type of sampling in your answer. (4)
4. Which of the following is a non-directional (two tailed) hypothesis?
A There is a difference in driving ability with men being better drivers than women
B Women are better at concentrating on more than one thing at a time than men
C Women spend more time doing the cooking and cleaning than men
D There is a difference in the number of men and women who participate in sports
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