When a survey is undertaken and it is not possible to cover the entire population, the marketing researcher has to answer a basic question - how large should the sample be ? the sample size decision is related directly to research cost, and therefore must be justified.
The researcher while deciding the appropriate size of the sample compromises all the factors affecting the sample size. The decision to decide the sample size must be scientifically made and should not be done arbitrarily because of the risks involved. The sample size should be neither too large nor too small.
Factors Determining Sampling Size
Sample size really depends on four factors:
* The number of groups and subgroups within the sample that will be analyzed.
- the value of the information in the study in general and the accuracy required of the results in particular.
- The third factors is the cost of the sample. A cost benefit analysis must be considered. A larger sample size can be justified if sampling costs are low than if sampling costs are high.
- The final factors is the variability of the population. If tall members of the population have identical opinions on an issue a sample of one is satisfactory. As the variability within the population increases the sample size also will need to be large.
Determining the Sample Size
There are two basic approaches to the problem to the sample size:
a. Ad hoc or practical approach
The former is widely used in marketing research ,
Ad hoc practical Methods: According to this approach, sample size of less than a few hundred units is not chosen. This is because when afield survey is undertaken interviewers are appointed trained and asked to conduct field investigations. Since al this would cost substantially it would not be worth it for the marketing researcher if only a small sample is chosen. A survey confined to a relatively small number of unit would mean a relatively high cost per interview. Another consideration in favour of selecting a reasonable size of sample in that it enables the researcher to test several hypotheses. This is especially true for sample in the sub group. such hypotheses can be tested with a high degree of is statistical significance when the sample size is reasonably large. Another practical consideration in case of a stratified sample is that the overall sample size is so fixed that the sample size within each stratum is not less than 30. A common practice in this regard is to determine the sample size of each stratum first and then add up the samples of all the strata to obtain the overall sample size.
Few common ad hoc methods for determining sample size are:
1.Rules and Thumb : One approach is to use come rules of thumb. Sudman suggests that the sample should be large enough enough so that when it is divided into group each group will have a minimum sample size of 100 or more.
Suppose that the opinions of citizens regarding municipal parks are desired. In particular estimation is to be made of the percentage who felt that tennis courts are needed suppose further that a comparison i s desired among those who (a) use parks frequently( c) use parks occasionally and (e) never use parks. Thus the sample size should be such that each of these groups has at least 100peopl. If the frequent park users the smallest group, are thought to be about 10 percent of the population then under simple random sampling size of 1000 would be needed to generate a group of 100 subjects.
In almost every study a comparison between group s provides useful information and is often the motivating reason for the study. It is therefore necessary to consider the smallest group and to make sure that it is of sufficient size to provide the needed reliability.
2.Budget Constraints : Often there is a strict budget constraint. A museum director might be able to spare only Rs. 50000 for a study and no more. If data analysis will require Rs. 1000and a respondent interview is Rs. 50 ,then the maximum affordable sample size is 80. The question then becomes whether a sample size of 80 is worthwhile or if the study should be changed or simply not conducted.
3.Comparable Studies : Another approach is to find similar studies and use sample sizes as a guide. The studies should be comparable in terms of the number of groups into which the sample is divided for comparison purpose. They also should have achieved a satisfactory level of reliability.