Repairs 327.67 376.68 392.52 443.14 342.62 476.16 324.74 338.98 433.45 526.37 362.42 448.76 335.27 350.94 291.81 467.8 474.48 354.15 420.11 416.04 321.86 303.73 301.06 279.24 327.94 281.74 393.35 265.16 350.3 123.88 254.59 309.57 208.73 223.34 319.26 414.3 245.8 365.37 308.46 353.67 388.06 401.24 311.13 252.33 348.88 282.31 251.56 250.32 338.67 388.24 342.19 Age 110 113 114 134 93 141 115 115 115 142 96 139 89 93 91 109 138 83 100 137 127 164 159 155 179 146 134 150 159 121 168 158 113 145 151 165 139 148 149 146 87 106 72 67 83 74 72 77 81 88 100 Machine 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 3 475.41 287.77 341.1 276.1 363.88 309.87 326.9 292.97 354.35 104 77 90 77 85 84 68 73 89 3 3 3 3 3 3 3 3 3 Refer to Exercise 16.100, where a simple linear regression model was used to analyze the relation-ship between welding machine breakdowns and the age of the machine. The analysis proved to be so useful to company management that it decided to expand the model to include other machines. Data were gathered for two other machines. These data as well as the original data were recorded in the following way: Column 1: Cost of repairs Column 2: Age of machine Column 3: Machine (1 = welding machine; 2 = lathe; 3 = stamping machine) a. Develop a multiple regression model. b. Interpret the coefficients. C. Can we conclude that welding machines cost less to repair than other machines? The president of a company that manufactures car seats has been concerned about the number and cost of machine breakdowns. The problem is that the machines are old and becoming quite unreliable. However, the cost of replacing them is quite high, and the president is not certain that the cost can be made up in today's slow economy. To help make a decision about replacement, he gathered data about last month's costs for repairs and the ages (in months) of the plant's 20 welding machines. a. Find the sample regression line. b. Interpret the coefficients. c. Determine the coefficient of determination, and discuss what this statistic tells you. d. Conduct a test to determine whether the age of a machine and its monthly cost of repair are linearly related. e. Is the fit of the simple linear model good enough to allow the president to predict the monthly repair cost of a welding machine that is 120 months old? If so, find a 95% prediction interval. If not, explain why not.