Part a)
Let pens be X and sells be Y. The Pearson correlation coefficient between X and Y is obtained as:
"\\sum(x_i - \\bar x) (y_i - \\bar y) = -632.5" "\\sum(x_i - \\bar x)^2=437.5" "\\sum(y_i - \\bar y)^2=920.8333"
Therefore
Null hypothesis, "H_0: r = 0"
Alternative hypothesis, "H_1: r \\not =0"
Since we have 12 data points, the degrees of freedom for the hypothesis test are:
The critical value associated with 10 degrees of freedom is "\\underset{-}{+} 0.576"
Since the correlation is greater than the critical value i.e "-0.99651 >0.576" , we can conclude that the correlation between pens and sells is significant
Part b)
Regression line for sells on pens
Using Excel, click on the "Data\\ Analysis\\ tab" , select "regression"
In the pop-up window, fill "Input\\ X\\ Range"
With the cell ranges containing pens and
"Input\\ Y\\ Range" with cell ranges containing sells.
Excel returns an
"Intercept\\ coefficient=82.6952"And
"Slope\\ coefficient=-1.4457"
The regression equation is therefore
Part c)
Weekly sells for 20 pens is
Part d)
The mean square error (MSE) gives an average of the error from the model
"=\\frac{6.41904}{6}=1.06984"
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