The research team thought that the life-cycle cost was related to the number of seats produced annually. To test this idea, they collected data for existing seats that had been manufactured for the CUP2 for the past ten years. The data is summarized in the table below.
year: 89 90 91 92 93 94 95 96 97 98
Number of seats 314 412 389 370 310 287 280 150 160 140
produced:
(in hundreds)
Life-cycle Cost: 395 370 380 381 390 400 395 420 430 450
(mean to nearest dollar)
A. Construct a scatter plot for the data. Does the relationship appear to be linear?
B. State appropriate null and alternate hypotheses with regard to correlation.
C. Compute the Pearson r.
D. Test it for significance at the .05 level. Based on the p-value, make a decision about the null hypothesis (Reject of Fail to Reject).
E. Compute the regression line for the data.
F. How much (what percent) of the variation is explained by the regression line?
G. According to the regression model, what is the predicted life-cycle cost if 460 seats are produced?