The sales manager of a retailer of KSI sunblock is monitoring the effects of its television advertising campaign. Over the last \(7\) weeks, different durations of television air time, \(x\) minutes, were used and the corresponding number of sales, \(y\), in hundreds of bottles of KSI sunblock, were recorded as follows:
\(x\) | \(8\) | \(11\) | \(15\) | \(18\) | \(20\) | \(22\) | \(25\) |
|---|---|---|---|---|---|---|---|
\(y\) | \(11.1\) | \(15.2\) | \(19.9\) | \(22.8\) | \(24.1\) | \(25.0\) | \(26.1\) |
Calculate the least squares estimates of \(a\) and \(b\), and the product moment correlation coefficient for the model that best fits the data set. [2]
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