For most of this book, we’ll be working on applications that do *linear regression*, a simple but informative statistic. Suppose that you have a series of data pairs, such as the quarterly sales figures for a particular department, shown in Table 2.1.

**Table 2.1. Quarterly Sales Figures for a Hypothetical Company (millions of dollars)**

Quarter | Sales |
---|---|

1 | 107.5 |

2 | 110.3 |

3 | 114.5 |

4 | 116.0 |

5 | 119.3 |

6 | 122.4 |

A *regression line* is the straight line that passes nearest all the data points (see Figure 2.1). The formula for such a line is *y = mx + b*, or the sales (*y*) for a given quarter (*x*) rise at a quarterly rate (*m*) from a base at “quarter zero” (*b*). We have the *x* and *y* values; we’d like to determine *m* and *b*.

**Figure 2.1. The ...**

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