You make the bold assumption that there is a linear relationship between number of ads and sales revenues. Find the intercept, b0, and the slope, b1, of the estimated regression equation that will minimize the sum of square residuals.
You make the bold assumption that there is a linear relationship between number of ads and sales revenues. Find the intercept, b0, and the slope, b1, of the estimated regression equation that will minimize the sum of square residuals.
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You make the bold assumption that there is a linear relationship between number of ads and sales revenues. Find the intercept, b0, and the slope, b1, of the estimated regression equation that will minimize the sum of square residuals.

Transcribed Image Text:The following six advertising campaigns show the number of ads (x) and the
resulting sales revenues (y) from each advertising campaign. Table 1 illustrates the data.
1.
TABLE 1. Sample data for sales (y) and number of ads(x)
Obs.
у
X; – x (x; – x)² yi - ỹ (X¡ – x)(y; – y)
e (yi - 7)? (ŷi – y)?
Vi – y)²
1
10
49
6 41
3
16
49
4
8 36
12
46
6.
8 43
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