2. The following data were collected last semester on ten students. Complete a multiple regression analysis in which you use AGE (A), MATH PROFICIENCY (MP) (on a 1 –10 scale), and GENDER (G) (0 = male, 1 = female) as predictors of FINAL EXAM (FE) performance. Do this analysis in SPSS and then answer the following questions.
Subject # |
A |
MP |
G |
FE |
1 |
35 |
8 |
1 |
90 |
2 |
31 |
6 |
0 |
88 |
3 |
26 |
5 |
1 |
84 |
4 |
33 |
7 |
0 |
91 |
5 |
28 |
3 |
1 |
78 |
6 |
32 |
5 |
1 |
92 |
7 |
29 |
7 |
0 |
92 |
8 |
39 |
6 |
1 |
87 |
9 |
37 |
6 |
0 |
92 |
10 |
38 |
7 |
0 |
89 |
2. The following data were collected last semester on ten students. Complete a multiple regression analysis in which you use AGE (A), MATH PROFICIENCY (MP) (on a 1 –10 scale), and GENDER (G) (0 = male...
Hello, appreciate if anyone could help me on Multiple Regression analysis. Thanks! Question 4 Use the multistep process to interpret the regression result below. This model has been run by a researcher trying to explain user pleasure of browsing Facebook. The independent variables are user perceptions of Perceived Usefulness, Complementary Convenience and Entertainment. Model Summary Change Statistics Std. Error R of the Adjusted R R Sig. F Change Model R df2 df1 Square Change Square Estimate Change Square 392 .097a...
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Price (in K) Sqft Age Features CornerCODE Corner_Label 310.0 2650 13 7 0 NO 313.0 2600 9 4 0 NO 320.0 2664 6 5 0 NO 320.0 2921 3 6 0 NO 304.9 2580 4 4 0 NO 295.0 2580 4 4 0 NO 285.0 2774 2 4 0 NO 261.0 1920 1 5 0 NO 250.0 2150 2 4 0 NO 249.9 1710 1 3 0 NO 242.5 1837 4 5 0 NO 232.0 1880 8 6 0 NO...