In survey research it is very rare for all respondents in a given population to be interviewed. We usually take a sample of that population. The reason why we can do this is because a sample can give us, not necessarily the accuracy of a census (or full count), but sufficient accuracy for prediction purposes. This is true if the sample is representative of the population from which it is drawn. There are various sampling methods that can be used if we wish to obtain a representative sample. Such samples can give, depending mainly on the size of the sample, results to given levels of precision.
How should I decide on the sample size for a survey? That is a question often posed by survey researchers to statisticians. It is difficult to answer simply as in market research we carry out surveys which more often than not carry a large number of different questions. There may be questions which are more important than others and hence need to be answered with a higher level of precision. A good starting point therefore is to consider the most important item to be measured by a proposed survey. For the moment we will assume that the survey is to be carried out using a Simple Random Sample and that the survey result is a percentage.
Typal analysis is a powerful tool for determining a structure within a large body of data . By studying and comparing the results of two series of experiments (random typology and typology of random numbers) we have been able to define two coefficients which measure informational content and the amount of structure for a given typology. The usefulness of these coefficients in solving the problems associated with typal analysis is demonstrated.