Sample size justification deals with the justification of the sample size. Sample size justification is very important because it affects the results of the research. If, for example, the sample size is too small, then even if everything else has been carried out perfectly, the inferences drawn will not be valid or perfect. On the other hand, sample size justification is also important in the case of a sample size being too large. In this case, if the sample size is too large, the results can also provide a false statistical inference. Therefore, sample size justification is important in order to make a valid inference about the product being tested. Sample size justification is important in the field of psychology, business and medicine and nursing.
In the field of psychology, sample size justification is important if one is trying to compute the difference of means from two populations using a t-test. Sample size justification implies that in this case, the sample size should be less than 30. Sample size justification is also important if one is trying to compute the difference of means from two populations using the z test. Sample size justification implies that in this case, the sample size should be more than 30. Sample size justification is also important in the case of regression analysis. Sample size justification is important if, for example, one is trying to predict the behavior of a child in his teenage years given some other dependent variables. Sample size justification implies that in regression analysis, there should be at least 10 samples for each independent variable.
In the field of business, sample size justification plays a crucial role in the case of market research study. Sample size justification is important in this case, when one is performing a problem of identification in market research study. Sample size justification implies that the minimum sample size should be around 500 from a population of the size of 1000-2500. Sample size justification is also important when one is performing problem solving in market research study. Sample size justification implies that the sample size should be around 200 from a population of the size of 300-500. For example, sample size justification is important, let’s say, if one is performing TV / radio advertising market research study. Sample size justification implies that the minimum sample size should be around 150 from a population of the size of 200-300. Sample size justification is equally important if one wants to test market audits. Sample size justification implies that the sample size of the stores should be around 10 from a population of 20 stores.
In the field of medicine / nursing, sample size justification is important when a researcher wants the curability effect of two drugs, say, drug A and drug B. Sample size justification implies that this test should be carried out on more than 150 patients, otherwise this may result in a Type II error. Thus, sample size justification can prevent a researcher from getting a Type II error, which is the most serious error in the field. If a researcher goes against the sample size justification in this case, i.e. by not conducting the test on 150 patients, then the result will say that there is no difference in drug A and drug B—and this is a serious error called Type II error. Thus, the researcher must deal properly with sample size justification.
It is important for a researcher to always keep sample size justification in mind. The researcher must always be aware of sample size justification, otherwise the results of their research will not be valid.
