Problem 5:
Y variable is VIAD. Two quantitative predictors IQM (X1) and IQF(X2). Categorical variable gender (represent indicators as ZF and ZM / one of the categories needs to be suppressed)
Note: ANACOVA model only appropriate as long as there is no interaction between the quantitative X’s and the categorical variable
| VIAD | IQM | IQF | Gender |
| -10 | 115 | 100 | Male |
| -4 | 112 | 110 | Male |
| 9 | 106 | 108 | Male |
| -15 | 123 | 135 | Male |
| -15 | 125 | 115 | Male |
| 5 | 105 | 112 | Male |
| -8 | 115 | 121 | Male |
| -4 | 122 | 132 | Male |
| -1 | 138 | 135 | Male |
| 13 | 110 | 126 | Male |
| 8 | 120 | 141 | Female |
| -5 | 130 | 128 | Female |
| 2 | 110 | 104 | Female |
| -7 | 113 | 98 | Female |
| 15 | 102 | 106 | Female |
| -10 | 141 | 130 | Female |
| -3 | 120 | 128 | Female |
| 10 | 113 | 105 | Female |
| 2 | 114 | 107 | Female |
| 4 | 102 | 111 | Female |
The regression model for testing the appropriateness of the ANCOVA model is:
VIAD = -2.47 + 17.47 IQM_102 + 1.97 IQM_105 + 5.97 IQM_106 + 9.97 IQM_110 - 7.03 IQM_112 + 9.47 IQM_113 + 10.0 IQM_114 - 12.03 IQM_115 + 10.47 IQM_120 - 7.03 IQM_122 - 18.03 IQM_123 - 18.03 IQM_125 + 3.0 IQM_130 - 4.03 IQM_138 - 2.0 IQM_141 - 5.50 Gender_Female + 5.50 Gender_Male
Problem 5: Y variable is VIAD. Two quantitative predictors IQM (X1) and IQF(X2). Categorical variable gender (represent indicators...