54 Chapter 2 Graphical Summaries of Data 0 1 2 3 4 5 6 7 7 6 5 4 3 2 1 0 Frequency Particulate Emissions Figure 2.7 The class width is too narrow. The jagged appearance distracts from the overall shape of the data. 0 2 4 6 8 35 30 25 20 15 10 5 0 Frequency Particulate Emissions Figure 2.8 The class width is too wide. Only the most basic features of the data are visible. data with a class width of 2.0. The number of classes is too small, so only the most basic features of the data are visible in this overly simple histogram. Choosing a large number of classes will produce a narrow class width, and choosing a smaller number will produce a wider class width. It is appropriate to experiment with various choices for the number of classes, in order to find a good balance. The following guidelines are helpful. Guidelines for Selecting the Number of Classes • For many data sets, the number of classes should be at least 5 but no more than 20. • For very large data sets, a larger number of classes may be appropriate. EXAMPLE 2.13 Constructing a histogram with technology Use technology to construct a frequency histogram for the emissions data in Table 2.7 on page 48. Solution The following figure shows the histogram constructed in MINITAB. Note that MINITABhas chosen a class width of 0.5.With this class width, there are two empty classes. These show up as a gap that separates the last two rectangles on the right from the rest of the histogram. Step-by-step instructions for constructing histograms with the TI-84 Plus and with MINITAB are given in the Using Technology section on pages 57 and 58.
navidi_monk_essential_statistics_1e_ch1_3
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