A simple linear regression model is employed to analyze the 24 monthly observations given in Table 13.4. Residuals are computed and are plotted versus time. The resulting residual plot is shown in Figure 13.30. Discuss why the residual plot suggests the existence of positive autocorrelation.
TABLE 13.4
Sales and Advertising Data for Exercise 13.63

FIGURE 13.30
Residual Plot for Exercise 13.63
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Monthly Total Sales, y 202.66 232.91 272.07 290.97 299.09 296.95 279.49 255.75 242.78 255.34 271.58 268.27 260.51 266.34 281.24 286.19 271.97 265.01 274.44 291.81 290.91 264.95 228.40 209.33 Advertising Expenditures, x 116.44 119.58 125.74 124.55 122.35 120.44 123.24 127.55 121.19 118.00 121.81 126.54 129.85 122.65 121.64 127.24 132.35 130.86 122.90 117.15 109.47 114.34 123.72 130.33 Month 10 12 13 14 15 16 17 18 19 20 21 23 24 4D o-10 0 5 10 15 20 25 Time