 The specific analysis performed on the subjects depends on the type of subjects, the type of questions being asked, and the purpose of the research.  When we gathered and tested all possible subjects from a known population we would use descriptive statistics to analyze our results.  Descriptive statistics require the testing of everyone in the population and are used to describe the qualities of the population in numerical format.  For example, we could say that the mean score on an IQ test for all third graders at Jefferson High School is 102.  We could also state that there is no difference between the IQs of boys and girls within our subjects if the data support these conclusions.

When we are using a sample of subjects smaller than the entire population, we must make some inferences using what we call inferential statistics.  Like any inferences, we also assume a certain degree of error when making determinations about a population based on a sample of that population.  Because of this, the results of inferential statistics are often stated within a predetermined level of confidence.

If we found that the mean of one group was 10 points higher than the mean of a second group in our work experience and college grades study, we could not assume that the population means are identical.  We could, however, state that the means of the entire population are likely to differ by five to 15 points or that there is a 95% probability that the means of the entire population differs by ten points.  In this sense, we are predicting the scores of the entire population based on the scores of our sample and stating them within a range or a predetermined level of confidence.  This allows us to include the likely error that occurs whenever an inference is made.