The data in the table are the selling prices z of a certain make and model of used car years old. Fit a curve of the form yo by means of the nonlinear sample regression equation 2=cd". (Hint: Write In 2= Inc+(Ind)=bo+b; ca.] PETE z (dollars) (years) 6307 3 5676 5 5749 5 co (years) 1 z (dollars) 5386 4976 4903 The equation in the form 2 = cd" is 2=x" (Round to four decimal places as needed.) D CEE

Table 2 shows a recent graduate’s credit card balance each month after graduation. a. Use exponential regression to fit a model to these data. b. If spending continues at this rate, what will the graduate’s credit card debt be one year after graduating?

Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?

Can the average rate of change of a function be constant?