HYPOTHESIS FOR BEGINNERS: A STEP BY STEP GUIDE ON APPLYING THE RIGHT HYPOTHESIS FOR A RESEARCH STUDY
Dec 28, 2014 By Japheth A. YayaTweet
Hypothesis is a testable prediction, a statement of specific results or a suggested answer to a research problem or a conjectural statement of the relationship between two or more variable being investigated or a deduction from a postulate (Akinade&Owolabi, 2009; Awoniyi, Aderanti&Tayo, 2011; Cherry, 2014).It can be regarded as the suggested answer to a research objective and problem. It is an idea or guess regarding how the researcher thinks the results of a study will look like. Simply put, it is a tentative assumption, supposition, guess, inference, explanation or prediction about some phenomenon that can be tested in a reasonable time frame. It is always put in declarative statement to relate the research variables to each other generally or specifically.While the hypothesis predicts what the researchers expect to see, the goal of research is to determine whether this guess is right or wrong (Cherry, 2014).
Types of Hypothesis
Basically, there are two types of hypotheses namely: Null and Alternative. Null hypothesis is stated in the negative form e.g. there is no significant relationship between employee motivation and job satisfaction of librarians in the university library. It is being denoted with Ho sign.The Alternative hypothesis is stated in the positive or affirmative form e.g. there is significant relationship between employee motivation and job satisfaction of librariansin the university library. It is being denoted with Hi sign. It can be noted here that it is not in all research that we formulate hypotheses; in some we have only research questions.
Sources of Hypotheses
Hypotheses could be derived from the following sources (Akinade&Owolabi, 2009):
- Directly from research variables
- Directly from research objectives
- Directly from research questions
- Directly from research designs
- Directly from findings of other studies
- Review of literatures
- From personal or practical experience or observation and analogy
- A haunch from a discrepancy, mismatch or feeling of incompatibility
- Logical reasoning; curiosity
- From something that needs a solution
- Suggestions from students or colleagues or subject experts
- General culture; and
- Disputation of findings in literature.
A testable hypothesis makes a statement about a presumed or theoretical relation between two or more variables (Kerlinger, 1986) – that can be observed or measured. Thus, a testable hypothesis should state or imply that the variables are observable and measurable. It should also specify the relation among the variables, e.g. higher grades are obtained after studying in the library than studying in the hall of residence.
Non-testable hypotheses may include, “abortion is wrong“, “stigmatizing ebola patient is bad”, “I seem to study better in the library than in your room” (Akinade&Owolabi, 2009, p. 19).
Characteristics of Good Hypotheses
According to Awoniyi et al (2011); Akinade and Owolabi (2009); Cherry (2014), each acceptable hypothesis should have the following features:
- It must provide a specific and adequate answer to a problem that is limited in scope (i.e. give only one answer to a problem at a time).
- It must be based on the research topic.
- It must include independent and dependent variables. It should be framed in a way that the expected relationship between independent and dependent variables are clearly stated.
- Hypotheses should be testable and measurable. One of the most common sources of difficulty for the student who embarks on research project is the selection of hypothesis that is not really testable.
- It should be correctly, clearly and precisely stated.
- It should state expected relationships between research variables. Hypotheses should be appropriate as a basis for research.
- It should be limited in scope. A common error of the research student in planning research is to develop hypotheses of global significance. Students should seek hypotheses that are relatively simple to test, and yet are highly significant.
- It should be consistent with most facts. Any hypothesis formulated as a basis of research must be consistent with a substantial body of established facts.
- The hypotheses selected should be amendable to testing within a reasonable time. Before any research is undertaken, the student should ask himself practical questions about whether he has the resources and time to undertake the investigation.
- Hypotheses must be testable or verifiable by independent researchers using identical conditions, so as to ascertain its validity.
- Hypotheses should be tested without violating ethical standards.
- Hypotheses should be operationally defined.
Misconceptions of the Hypotheses
- Hypotheses must always be stated in a positive mode.
- Each study must have a number of hypotheses usually five or more, to be respectable.
- Hypotheses must be upheld by the research data.
- There is usually no need to formulate hypotheses in historical studies.
All the aforementioned misconceptions are fallacies which must be jettisoned while carrying out a research work.
Testing of Hypotheses
The following steps should be observed when testing any research hypothesis (Awoniyi et al, 2011):
- Formulate a null hypothesis (Ho). Hypothesis can either be accepted or rejected.
- Set up a suitable level of significance. It means the level at which to accept or reject null hypothesis. It is conventional among researchers to accept or reject hypothesis at 0.05 or 0.01 level of significance. This implies that the researcher is allowed some margin of error in his research result. For instance 0.05 level of significance implies that the researcher allows 5% error margin and he is 95% confident of whatever result or conclusion is drawn from his study while for 0.01 level of significance the researcher allows only 1% error margin and he is 99% confident of the result or conclusion drawn from his study.
- Select appropriate statistical techniques. There are many techniques from which a researcher can choose the most appropriate to test his hypothesis such as in the following cases:
- When hypothesis has to do with a large sample (i.e. more than 30) and it is testing for a significant difference between two variables, the z - test implying normal distribution is used and when a sample is small (less than 30), t – test is employed.
- When the hypothesis is started to test for relationship between two variables, the Pearson product moment correlation co-efficient is used, when there is equal distribution of subjects for non-parametric variables, the Spearman rank order correlation coefficient is used.
- When the hypothesis is stated to test differences or relationship between two or more independent variables and one dependents variable, the analysis of variance (ANOVA) or analysis of covariance (ANCOVA) could be employed.
- Multivariate Analysis of Covariance (MANCOVA) is used when there are two or more independent variables against two or more dependent variables.
- Chi-square test is applied to data derived from normal scale of measurement, that is, data obtained in form of frequency counts. It is used for testing hypothesis concerning the difference between sample frequency observed within certain categories and those expected with the categories and those expected with the categories. Chi-square can only indicate whether or not a set of observed frequencies differ significantly from the corresponding set of expected frequencies.
Akinade, E.O. &Owolabi, T. (2009).Research Methods: A Pragmatic Approach for
Social Sciences, Behavioural Sciences and Education. Lagos: Connel Publications.
Awoniyi, S.A., Aderanti, R.A. &Tayo, A.S. (2011).Introduction to Research Methods.
Ibadan: Ababa Press.
Cherry, K. (2014).What Exactly Is a Hypothesis? Retrieved from http://psychology.about.com/od/hindex/g/hypothesis.htmon 22/12/2014.
Kerlinger, F.N. (1986). Behavioural Research: A Conceptual Approach. New Delhi: Sterling