ABSTRACT
As stated earlier, descriptive statistics is used to describe a set of data in terms of its frequency of occurrence, its central tendency, and its dispersion. Although the description of data is important and fundamental to any analysis, it is not sufficient to answer many of the most interesting problems that researchers encounter. Consider an experiment in which a researcher is interested in finding whether a particular drug can improve people’s memory. The researcher offers the drug to one group but not to the control group, and then compares the means of the two groups on a memory test. Descriptive statistics will not tell the researcher, for example, whether the difference
difference between two obtained sample means, is small enough to be explained by chance alone or whether it represents a true difference that might be attributable to the effect of the experimental treatment, i.e., the drug. To address these issues, the researcher must move beyond descriptive statistics and into the realm of inferential statistics, and, particularly, on to the statistical procedures that can be employed to arrive at conclusions extending beyond the sample statistics themselves. A basic aim of inferential statistics then is to use the sample scores for
hypothesis testing
.
