Chapter 15.3, Problem 14E

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?

Given below are results from the regression analysis where the dependent variable is the number of weeks a worker is unemployed due to a layoff​ (Unemploy) and the independent variables are the age of the worker​ (Age), the number of years of education received​ (Edu), the number of years at the previous job​ (Job Yr), a dummy variable for marital status​ (Married: 1=​married, 0=​otherwise), a dummy variable for head of household​ (Head: 1=​yes, 0=​no) and a dummy variable for management position​ (Manager: 1=​yes, 0=​no). We shall call this Model 1. The coefficient of partial determination ​(R2Yj.(All variables except j)​) of each of the six predictors​ are, respectively,​ 0.2807, 0.0386,​ 0.0317, 0.0141,​ 0.0958, and 0.1201. Model 2 is the regression analysis where the dependent variable is Unemploy and the independent variables are Age and Manager. The results of the regression analysis are given. Refer to model 1. Which of the following is the correct null hypothesis to test…

In the packaging department of a large aircraft parts​ distributor, a fairly reliable estimate of packaging and processing costs can be determined by knowing the weight of an order.​ Thus, the weight is a cost driver that accounts for a sizable fraction of the packaging and processing costs at this company. Data for the past 10 orders are given as​ follows: a. Estimate the b0 and b1 ​coefficients, and determine the linear regression equation to fit these data. b. What is the correlation coefficient (R​)? c. If an order weighs 205 lb, how much should it cost to package and process​ it?                Packaging and Processing Cost​ ($), y Weight​ (Pounds), x 99 240 111 275 86 210 85 185 121 315 114 300 111 285 100 270 109 275 85 200