Suppose that a term in a logistic regression equation is 0.687*MallTrips, as in Figure 17.17. Explain, exactly what this means.

Figure 17.17

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Н 8 Logistic Regression for Have Tried Yes 9 Summary Measures This is the output from using all explanatory variables. You can run the logistic regression again, deleting variables with high p-values, but the basic results don't change substantially. 10 Null Deviance 1165.604813 11 Model Deviance 687.9428839 12 Improvement 13 p-Value 477.6619292 <0.0001 14 15 Standard Wald Lower Upper Exp(Coef) Coefficient p-Value 16 Regression Coefficients Value Error Limit Limit 17 Constant 0.909698289 0.0052 --0.757579042 -2.540587689 -2.79278055 -4.323596336 0.078820065 18 Age -0.069688555 0.010808445 -0.090873108 -0.048504003 -6.447602252 <0.0001 0.932684254 19 Weight 0.007033414 0.014578691 0.003849631 1.82703581 0.0677 -0.000511863 1.007058206 20 Income 4.76283E-06 0.2076 -2.64471E-06 3.77935E-06 1.260222403 1.21704E-05 1.000004763 21 Car Value 0.1911 2.04171E-05 -1.307318278 -6.67092E-05 0.999973309 -2.66917E-05 1.33259E-05 22 ICC Debt 0.852024709 0.3942 -0.000101272 0.000257027 1.00007788 7.78774E-05 9.14027E-05 23 Mall Trips 1.987754476 0.687005598 <0.0001 0.569867539 0.804143656 0.059764316 11.49524745 24 Pay Type Salaried 6.032913283 <0.0001 0.899758382 1.765736273 0.220912727 3.791445433 1.332747327 25 Gender Male 0.191544317 0.1822 0.630969333 0.255542473 1.334116706 -0.119884388 1.291161851 26 Live Alone Yes 1.322630127 0.283886309 <0.0001 1.879047292 4.659013441 0.766212962 3.75328001 27 Dwell Type Condo 28 Dwell Type Home 0.7686 -0.080928114 0.275087202 -0.294190764 0.922259987 -0.620099029 0.458242801 0.248863714 0.710114914 0.176721835 0.4776 -0.311051044 0.664494713 1.193299112