Statistics is the science of data. An important aspect of dealing with data is organizing and summarizing the data in ways that facilitate its interpretation and subsequent analysis. This aspect of statistics is called **descriptive statistics,** and is the subject of this chapter. For example, in Chapter 1 we presented eight observations made on the pull-off force of prototype automobile engine connectors. The observations (in pounds) were 12.6, 12.9, 13.4, 12.3, 13.6, 13.5, 12.6, and 13.1. There is obvious variability in the pull-off force values. How should we summarize the information in these data? This is the general question that we consider. Data summary methods should highlight the important features of the data, such as the middle or central tendency and the variability, because these characteristics are most often important for engineering decision making. We will see that there are both numerical methods for summarizing data and a number of powerful graphical techniques. The graphical techniques are particularly important. Any good statistical analysis of data should always begin with **plotting the data.**

LEARNING OBJECTIVES

After careful study of this chapter you should be able to do the following: ...

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