ABSTRACT
References .............................................................................................................................................. 205 Exercises ............................................................................................................................. 205
Statistical inference was originally developed to estimate the parameters of a parent population by using the results found in a single random sample. As discussed in Chapters 7 and 8, the estimated parameters were the location of a point, such as the parametric mean or proportion, and the magnitude of a confidence interval surrounding the point. (In statistical parlance, these inferences are often called
point estimation
and
interval estimation
.) The inferential strategies were originally developed for use with random sampling only, but were later extended for their now common application to evaluate stability in single groups of data that were
not
obtained as random samples. This chapter is devoted to another type of inference, particularly common in medical research and
literature today, that is also an extension of the original methods for making estimates from a single random sample. The additional inferential activity, which is called
hypothesis testing
, uses the same basic strategy as before, but the “parameter” being estimated is the “value” of a mathematical hypothesis. The new process involves three main steps: (1) making a particular mathematical assumption, called a
null hypothesis
, about a parameter for the observed results; (2) appraising what happens when the observed results are rearranged under that hypothesis; and (3) deciding whether to reject or concede the hypothesis.
