We have been assigned to determine how the total weekly production cost for Widgetco depends on the…

We have been assigned to determine how the total weekly production cost for Widgetco depends on the number of widgets produced during the week. The following model has been proposed:

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Y = β0 + β1X + β2X2 + β3X3 + ε

where X = number of widgets produced during the week and Y = total production cost for the week. For 15 weeks of data, we found that SSR = 215,475 and SST = 229,228. For this model, we obtain the following estimated regression equation (t-statistics for each coefficient are in parentheses):

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a For α = 0.10, test H0: βi = 0 against Ha: βi ≠ 0 (i = 1, 2, 3).

b Determine R2 for this model. How can the high R2 value be reconciled with the answer to part (a)?

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