A hypothesis is a tool of quantitative studies. It is a tentative prediction regarding the relationship between the variables which are being studied. The key work that the hypotheses do is that it translates the research question into a prediction of the outcomes that can be expected from it. The entire research is done as an attempt to approve or disapprove the hypotheses.
In order to be complete, it is important that a hypotheses includes these three main components:
- The variables
- The Population
- The relationship
The key features of hypotheses are:
- Stated clearly by using the appropriate terminology
- It should be a clear about the relationship between the variables
- It should be having definable, limited scope
There is more than one type of hypotheses. They are:
- Simple Hypotheses: These hypotheses help to predict the relationship between a single independent variable (IV) on one side and a dependant variable(DV).
- Complex Hypotheses: This kind of hypotheses helps to predict the relationship that is there between more than two or two independent variable and likewise two or more than two dependant variable.
- Directional Hypotheses: These kinds of hypotheses are drawn from theory. These imply that the researcher is committed to a particular kind of outcome. These kind of hypotheses
- Non-directional Hypotheses: These kinds of hypotheses are used when there is little or no theory or when the findings are contradictory to previous study. They may have impartial implication and do not stipulate the direction of the relationship.
- Associative and causal hypotheses: These kind of hypotheses propose relationships between two variables. In this case when one variable changes the other one also changes.
- Null Hypotheses: As the name is indicative, they are used when the researcher insists that there is no relationship between the variables or when the empirical data is inadequate to state any kind of hypotheses. Null hypotheses can be simple, complex, causal and associative.
- Testable Hypotheses: It includes those variables that can be measured or have the capacity to be manipulated. Their task is to predict a relationship on the basis of data.