Hypothesis testing is used in research to agree or disagree with the research hypothesis that the researcher has formulated for his research. It is a statistical procedure that infers whether the research hypothesis is valid or not. To understand the role of hypothesis in research methodology one should have knowledge about the types and errors of testing a hypothesis.
What is a hypothesis
A hypothesis is a hunch, proposition or assumption, the basis of which the researcher carry on the research. A hypothesis brings a focal point to the research but regardless of its importance a research can be conducted without a valid hypothesis. Webster dictionary defines a hypothesis as a proposition, condition, or principle which is assumed, perhaps without belief, in order to draw out its logical consequences and by this method to test its accord with facts which are known or may be determined.
Types of hypothesis
In any research, there is one hypothesis that you seek to confirm or deny through your research. However, there are two categories of hypothesis and these categories are classified on the basis of the wording that we use in the formulation of the hypothesis. These two types are known as research hypothesis and alternate hypothesis.
A research hypothesis shows a comparison or a relationship between different variables. A research hypothesis is opposite of the alternate or null hypothesis. The research hypothesis is the actual hypothesis the researcher formulates and he is interested in knowing about. Acceptance of the research hypothesis through statistical procedures shows that the researcher made the right assumptions.
An alternate hypothesis is opposite of the research hypothesis. An alternate hypothesis is also called as the null hypothesis and it shows the relationship among variables when the research hypothesis is proved wrong.
Errors in testing a hypothesis
A hypothesis can be proven true or false at the completion of the study. There might be many reasons that a hypothesis is proven false. In research, there is always some chances of error in testing a hypothesis this error can be attributed to nay of the reasons that will be mentioned in detail below. There can be two types o errors in testing a hypothesis in the research: type I error and type II error.
A type I error means the rejection of a null hypothesis when it is true.
A type II error means acceptance of a null hypothesis when it is false.
The chances of error can be minimized by avoiding the following while conducting a research study:
- The study design should be selected with great caution, the researcher can select a study design that does not best suits the research and the hence the results will not be correct. This can also create study design bias in the research. A novice researcher may find it difficult to understand which design to select but he/she can get help from their research supervisors or other people who know about the subject area.
- The sampling procedure can also be the reason why the error happens in testing the hypothesis. Sampling is an important step in the research and the investigator should select the right and appropriate sampling procedure. Where possible he/she should prefer randomization over the non-random selection of sampling. However, random sampling is not always possible and in some cases, the researcher selects a sample non-randomly due to many reasons. Regardless of whether it is random or non-random the procedure of sampling should be free of bias and should follow a valid process.
- Another reason can be that data collection is not done properly.
- The data analysis should also be done without bias to avoid chances of errors.