21. Which SPSS regression METHOD of variable selection or entry produced the two output tables below? Model Summary Adjusted R Std. Error of the Model R R Square Square Estimate 22. What is the single most important 783 613 .609 15760.006 predictor of SALARY? .916 839 836 10207.659 .9495 .901 898 8046.186 957d 916 .913 7456.663 .9610 923 .919 7174.390 928 .923 6980.430 a. Predictors: (Constant), EXP b. Predictors: (Constant), EXP, GEN_SUP C. Predictors: (Constant), EXP, GEN_SUP, EDUC 23. Which variable has been d. Predictors: (Constant), EXP, GEN_SUP, EDUC, ASSETS excluded from every model? e. Predictors: (Constant), EXP, GEN_SUP, EDUC, ASSETS, NONSUP f. Predictors: (Constant), EXP, GEN_SUP, EDUC, ASSETS, NONSUP, GENDER Excluded Variables* Collinearity Partial Statistics Model Beta In Sig. Correlation Tolerance EDUC 2015 3.359 001 323 24. What type of term or variable is 1.000 GENDER .357b 6.888 000 573 .998 the one that has been excluded NONSUP .245b 4.221 100 .394 1.000 ASSETS .190 (simple, interaction, cubic, etc.)? 3.157 002 .305 1.000 EXPSQ .312b 1.224 224 123 060 GEN_SUP 477 11.688 000 765 993 EDUC 250 7.753 000 621 .990 GENDER .0175 289 .773 030 .462 NONSUP 0595 1.329 .187 134 830 ASSETS 137' 3.530 001 339 .987 EXPSQ 092* 551 583 056 060 25. What is the most logical reason GENDER -.046 -.962 339 -.098 .449 NONSUP 103 that this variable has been excluded 3.020 .003 .296 .811 ASSETS 123# 4.096 .000 .387 .983 from every model? EXPSQ 007 052 959 005 059 GENDER -.045 -1.014 .313 -.104 .449 NONSUP .094 2.936 .004 .290 .806 EXPSQ .082 -.657 513 -.068 057 GENDER 185 2.509 .014 252 .142 EXPSQ -.102f -.853 396 ..088 057 EXPSQ -.0909 -.776 440 -.081 057 - 4