We cannot conclude that either β0 or β1 are equal to zero, where β0 is the estimated price for a bicycle weighing zero pounds and β1 is the estimated change in price for a one pound weight increase. Both interpretations are reasonable.
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In a simple linear regression predicting price from weight, β0 is the intercept (predicted price when weight = 0 pounds) and β1 is the slope (the predicted change in price for each additional pound of weight). Show more…
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Racing Bike Significance of Weight on cost. In exercise $20,$ data on $x=$ weight (pounds) and $y=$ price (\$) for 10 road-racing bikes provided the estimated regression equation $\hat{y}=28,574-1439 x$ ( Bicycling website). For these data $\mathrm{SSE}=7,102,922.54$ and $\mathrm{SST}=52,120,800 .$ Use the $F$ test to determine whether the weight for a bike and the price are related at the .05 level of significance.
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The following data on x = weight (pounds) and y = price ($) for ten road-racing bikes provided the estimated regression equation ŷ = 28,574 – 1439x (Bicycling website). For these data SSE = 7,102,922.54 and SST = 52,120,800. Use the F test to determine whether the weight for a bike and the price are related at the 0.05 level of significance. Click on the datafile logo to reference the data. DATA file Calculate the value of the test statistic (to 1 decimal). The p-value is - Select your answer - . Use Table 4 of Appendix B. What is your conclusion? - Select your answer -
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