Chapter 1 made a distinction between a population and a sample and noted that a fundamental issue is understanding the extent to which inferences about a population can be made based on a sample. The focus in this chapter is on numerical methods for summarizing a sample. Chapters 4 and 5 describe the key components that will be needed to make inferences about the population.

To help motivate this chapter, imagine a study conducted on the effects of a drug designed to lower cholesterol levels. The study begins by measuring the cholesterol level of 171 participants and then measuring each participant's cholesterol level after 1 month on the drug. Table 2.1 shows the change between the two measurements. (The data are stored in the file ibtable2_1_dat.txt, which can be downloaded from the author's web page as described in Section 1.5.) The first entry is c02-math-0001, indicating that the cholesterol level of this particular individual decreased by 23 units. Further imagine that a placebo is given to 176 participants, resulting in the changes in cholesterol as shown in Table 2.2. Although we have information on the effect of the drug, there is the practical problem of conveying this information in a useful manner. Simply looking at the values, it is difficult determining how the experimental drug compares to the placebo. In general, how might we summarize the ...

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