In: Statistics and Probability
The data from data257.dat contains information on 78 seventh-grade students. We want to know how well each of IQ score and self-concept score predicts GPA using least-squares regression. We also want to know which of these explanatory variables predicts GPA better. Give numerical measures that answer these questions. (Round your answers to three decimal places.)
gpa iq gender concept 1 7.94 125 2 41 2 8.292 115 2 69 3 4.643 122 2 28 4 7.47 128 2 50 5 8.882 121 1 51 6 7.585 110 2 69 7 7.65 94 2 68 8 2.412 74 2 42 9 6 82 1 59 10 8.833 126 2 63 11 7.47 107 1 55 12 5.528 108 1 52 13 7.167 101 2 58 14 7.571 103 1 81 15 4.7 111 1 40 16 8.167 115 1 61 17 7.822 106 1 64 18 7.598 111 1 68 19 4 99 2 33 20 6.231 97 1 53 21 7.643 117 2 59 22 1.76 92 2 19 24 6.419 102 1 72 26 9.648 121 2 44 27 10.7 136 1 43 28 10.58 122 2 60 29 9.429 116 2 55 30 8 112 2 64 31 9.585 129 2 63 32 9.571 113 1 73 33 8.998 137 1 60 34 8.333 129 1 69 35 8.175 119 2 60 36 8 87 2 61 37 9.333 122 1 71 38 9.5 102 2 53 39 9.167 117 2 68 40 10.14 130 1 49 41 9.999 114 1 64 43 10.76 108 2 57 44 9.763 109 2 80 45 9.41 112 2 66 46 9.167 113 2 53 47 9.348 115 2 76 48 8.167 121 2 59 50 3.647 103 2 47 51 3.408 102 1 50 52 3.936 102 2 48 53 7.167 117 2 34 54 7.647 115 2 49 55 .53 90 2 15 56 6.173 112 2 51 57 7.295 100 2 52 58 7.295 119 1 74 59 8.938 113 1 64 60 7.882 107 1 57 61 8.353 120 2 58 62 5.062 79 2 34 63 8.175 113 2 56 64 8.235 93 2 48 65 7.588 91 2 42 68 7.647 122 2 44 69 5.237 107 1 54 71 7.825 121 2 91 72 7.333 108 1 66 74 9.167 117 2 67 76 7.996 110 2 49 77 8.714 110 1 62 78 7.833 106 1 65 79 4.885 106 2 62 80 7.998 126 1 83 83 3.82 101 2 53 84 5.936 100 1 52 85 9 104 1 56 86 9.5 113 1 83 87 6.057 109 2 60 88 6.057 104 1 62 89 6.938 119 2 48
(Regressor: IQ) R 2
=
(Regressor: Self-Concept) R 2
=
IQ
SUMMARY OUTPUT | |||||
Regression Statistics | |||||
Multiple R | 0.576383433 | ||||
R Square | 0.332217862 | ||||
Adjusted R Square | 0.323431255 | ||||
Standard Error | 1.726965757 | ||||
Observations | 78 | ||||
ANOVA | |||||
df | SS | MS | F | Significance F | |
Regression | 1 | 112.7636762 | 112.7636762 | 37.80957304 | 3.34928E-08 |
Residual | 76 | 226.6632152 | 2.982410726 | ||
Total | 77 | 339.4268914 | |||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | |
Intercept | -3.363963213 | 1.76894641 | -1.901676159 | 0.061003464 | -6.887125326 |
iq | 0.097946234 | 0.015928939 | 6.148948938 | 3.34928E-08 | 0.066221002 |
Concept
SUMMARY OUTPUT | |||||
Regression Statistics | |||||
Multiple R | 0.545796308 | ||||
R Square | 0.29789361 | ||||
Adjusted R Square | 0.288655368 | ||||
Standard Error | 1.770792974 | ||||
Observations | 78 | ||||
ANOVA | |||||
df | SS | MS | F | Significance F | |
Regression | 1 | 101.1131019 | 101.1131019 | 32.24570326 | 2.36652E-07 |
Residual | 76 | 238.3137895 | 3.135707757 | ||
Total | 77 | 339.4268914 | |||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | |
Intercept | 2.704030958 | 0.858895432 | 3.148265618 | 0.002347232 | 0.993392452 |
concept | 0.08333309 | 0.014675117 | 5.678530027 | 2.36652E-07 | 0.054105062 |
R^2 of IQ = 0.332217
R^2 of concept = 0.297893