The second important consideration in the formulation of a research problem in quantitative research is the construction of a hypothesis. Hypotheses bring clarity, specificity and focus to a research problem, but are not essential for a study. You can conduct a valid investigation
without constructing a single formal hypothesis. On the other hand, within the context of a research study, you can construct as many hypotheses as you consider to be appropriate. Some believe that one must formulate a hypothesis to undertake an investigation; however, the author does not hold this opinion. Hypotheses primarily arise from a set of ‘hunches’ that are tested through a study and one can conduct a perfectly valid study without having these hunches or speculations. However, in epidemiological studies, to narrow the field of investigation, it is important to formulate hypotheses.
The importance of hypotheses lies in their ability to bring direction, specificity and focus to a research study. They tell a researcher what specific information to collect, and thereby provide greater focus.
Let us imagine you are at the races and you place a bet.You bet on a hunch that a particular horse will win. You will only know if your hunch was right after the race. Take another example. Suppose you have a hunch that there are more smokers than non-smokers in your class. To test your hunch, you ask either all or just some of the class if they are smokers. You can then conclude whether your hunch was right or wrong.
Now let us take a slightly different example. Suppose you work in the area of public health. Your clinical impression is that a higher rate of a particular condition prevails among people coming from a specific population subgroup. You want to find out the probable cause of this condition. There could be many causes. To explore every conceivable possibility would require an enormous amount of time and resources. Hence, to narrow the choice, based on your knowledge of the field, you could identify what you assume to be the most probable cause. You could then design a study to collect the information needed to verify your hunch. If on verification you were able to conclude that the assumed cause was the real cause of the condition, your assumption would have been right.
In these examples, you started with a superficial hunch or assumption. In one case (horse racing) you waited for the event to take place and in the other two instances you designed a study to assess the validity of your assumption, and only after careful investigation did you arrive at a conclusion about the validity of your assumptions.
Hypotheses are based upon similar logic. As a researcher you do not know about a phenomenon, a situation, the prevalence of a condition in a population or about the outcome of a programme, but you do have a hunch to form the basis of certain assumptions or guesses. You test these, mostly one by one, by collecting information that will enable you to conclude if your hunch was right. The verification process can have one of three outcomes. Your hunch may prove to be: right, partially right or wrong. Without this process of verification, you cannot conclude anything about the validity of your assumption.
Hence, a hypothesis is a hunch, assumption, suspicion, assertion or an idea about a phenomenon, relationship or situation, the reality or truth of which you do not know. A researcher calls these assumptions, assertions, statements or hunches hypotheses and they become the basis of an enquiry. In most studies the hypothesis will be based upon either previous studies or your own or someone else’s observations.
There are many definitions of a hypothesis. According to Kerlinger, ‘A hypothesis is a conjectural statement of the relationship between two or more variables’ (1986: 17). Webster’s Third New International Dictionary (1976) 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.
Black and Champion define a hypothesis as ‘a tentative statement about something, the validity of which is usually unknown’ (1976: 126). In another definition, Bailey defines a hypothesis as:
a proposition that is stated in a testable form and that predicts a particular relationship between two (or more) variables. In other words, if we think that a relationship exists, we first state it as a hypothesis and then test the hypothesis in the field. (1978: 35)
According to Grinnell:
A hypothesis is written in such a way that it can be proven or disproven by valid and reliable data — it is in order to obtain these data that we perform our study. (1988: 200)
From the above definitions it is apparent that a hypothesis has certain characteristics:
- It is a tentative proposition.
- its validity is unknown.
- In most cases, it specifies a relationship between two or more variables.
Source: Kumar Ranjit (2012), Research methodology: a step-by-step guide for beginners, SAGE Publications Ltd; Third edition.
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