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CASE 15.2 INTEGRATED CASE Auto Concepts Segmentation Analysis IBM SPSS It is Monday, and today is your first day in your new mar target market definitions for each of the possible models. keting internship. After a rigorous application and review That is, using multiple regression analysis as a screening process including two grueling interviews with Cory Rog device, we need to identify the significant demographic and ers and Celeste Brown, you have been hired by CMG attitudes about global warming that uniquely define these Research. It is 9:00 a.m., and you are in Rogers's office preference segments." along with Brown. Cory says, We know that it is just your Celeste then says, We can go to the office where I first day as the CMG Research marketing intern, but we can give you a copy of the SPSS dataset, and, as you know, are getting bogged down with a lot of work that must be you can use SPSS Variable View or Utilities- Variables to completed very quickly or our clients will be unhappy. As see the code book for this survey." Cory ends the meeting I indicated to you a few days ago when I let you know that by saying, Great. I am sure that you will do a fantastic job we chose you to be this year's marketing intern, Celeste with this assignment. Celeste and I have to catch a flight in and I were very impressed with your command of SPSS a couple of hours, and we will be out of town for the next and your understanding of more advanced statistical analy three days. But you can call, text, or email. Let's set a meet- ses such as regression and analysis of variance. So, we are ing for 9:00 a.m. on Thursday, and you can show us what going to let you show us your stuff right away. you have found." Cory continues, We are in the final stages of a major Your task as the new CMG marketing intern: Use survey that we conducted for Auto Concepts. They have five the AutoConcepts. Recoded.sav data file. The dataset is automobile models under consideration for multimillion "recoded" with midpoint values for town size, education, dollar development. We have provided them with a great and so on, so these variables are now scale variables that deal of analysis, and they are in the process of narrowing conform to the requirements for regression analysis. Per- down the development list. I would like to give them one form the proper analyses to identify the salient demographic more set of findings. Specifically, I would like to give them and/or attitude factors that are related to preferences for REVIEW QUESTIONS/APPLICATIONS 401 each of the automobile models under consideration. With each automobile model, prepare a summary that: 1. Lists the statistically significant independent variables (use 95% level of confidence). 2. Interprets the direction of the relationship of each statistically significant independent variable with respect to the preference for the automobile model concerned. 3. Identifies or distinguishes the relative importance of each of the statistically significant independent variables. 4. Assesses the strength of the statistically significant independent variables as they join to predict the prefer- ences for the automobile model concerned. Coefficients Model Unstandardized Coefficients t Sig Standardized Coefficients B Std. Error Beta 6.981 .506 13.795 000 3.694E-007 .000 101 3.383 001 -1.315 .098 - 531 -13.442 .000 - 339 .115 - 086 -2.953 .003 5 -026 .004 - 260 -6.220 .000 -219 042 - 291 -5.207 000 3.073E-006 .000 .075 1.920 .055 .119 .039 . 164 3.016 .003 a. Dependent Variable: Desirability: 1 Seat Motorcycle Electric Model Summary Madel 1 Model Summary Adjusted R Square Square 266 268 266 259 266 259 265 259 264 259 R 516 516 516 515 514" 2 3 4 5 Sto Error of the Estimate 1.060 1 060 1 059 1 059 1.060 Coefficients Model Unstandardized Coefficients Sig Standardized Coefficients B Std. Error Beta 3.253 280 11.604 000 1.701E-006 000 374 13.988 .000 -532 107 - 172 4.984 .000 1.536 127 313 12.132 .000 --014 005 - 112 -3.032 002 6.277E-006 .000 - 123 -3.656 000 .480 052 415 9.295 000 - 564 .044 - 523 -12.733 000 a. Dependent Variable: Desirability: 2 Seat Runabout Sport Electric Model 1 2 Model Summary Adjusted R R Square Square 425 418 425 419 425 419 424 419 422 418 R .652 6526 652 6510 .650* 3 Std. Error of the Estimate 1.172 1.171 1.171 1.171 1.172 4 5 Model Unstandardized Coefficients t Standardized Coefficients Sig B Std. Error Beta 2.073 .673 3.080 .002 -7.911E-007 .000 - 140 -5.611 .000 -1.479 .126 - 384 -11.768 .000 .318 .174 052 1.830 .067 - 147 .057 3 -.074 -2.572 010 - 096 005 -619 -17.725 .000 .465 061 396 7.591 .000 -1.137E-005 .000 -178 -5.503 .000 .068 -306 -6.520 000 .657 056 583 11.710 .000 Dependent Variable: Desirability: 2 Seat Runabout Hatchback Gasoline Hybrid Model Summary Model 1 R 7079 R Square 500 500 499 Adjusted R Square 494 .495 .495 Std. Error of the Estimate 1.359 1.359 1.359 .7070 2 3 .707 Coefficients Model Unstandardized Coefficients t Sig Standardized Coefficients B Std. Error Beta 4.315 608 -7.100 .000 1.476E-006 .000 282 11.371 .000 469 .116 132 4.037 .000 - 440 .161 -078 -2.742 006 220 .053 .119 4.145 .000 .056 .005 .391 11.244 .000 .151 .052 .139 2.893 004 1.991E-005 .000 338 10.459 .000 .182 .048 175 3.809 .000 -.086 .036 -074 -2.385 .017 a. Dependent Variable: Desirability: 4 Seat Economy Diesel Hybrid Model Surinary Model 1 R 707" Adjusted R Square 494 495 495 R Square 500 .500 499 Std. Error of the Estimate 1.257 1.257 1.256 2 3 7076 .707 Coefficients Model Unstandardized Coefficients Sig Standardized Coefficients B Std. Error Beta 1.222 .302 4.049 .000 -7.532E-007 .000 - 175 -5.905 .000 275 .113 094 2.439 015 .131 044 .086 2.948 003 5 055 005 465 11.050 .000 -6.185E-006 .000 - 128 -3.463 .001 - 087 .044 -080 -1.993 047 .120 032 .152 3.770 .000 a. Dependent Variable: Desirability: 5 Seat Economy Gasoline Model Summary Model 1 R Square 258 Adjusted R Square 249 250 Std. Error of the Estimate 1.259 1.258 1.257 2 R .507 .5076 5070 .5070 505 258 3 .258 257 255 .251 251 4 1.257 5 250 1.258