Part c. Predict the corresponding probabilities for a member on a family plan.
40-year-old
60-year-old
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A B C D Loyal Age Income Plan 2 0 39 134 Single 57 120 Family 1 72 75 Single 1 71 143 Single 1 25 75 Single 1 44 149 Single 21 113 Family 1 26 87 Family 10 63 44 Family 11 0 37 44 Single 12 1 65 138 Family 13 43 138 Family 14 0 66 96 Family 15 1 21 91 Family 16 70 59 Single 17 0 39 31 Single 18 0 39 50 Single 19 0 43 85 Family 20 65 53 Single 21 1 73 119 Single 22 1 71 63 Family 23 0 72 51 Single 24 1 53 108 Single 25 0 60 46 Family 26 1 60 119 Single 27 0 21 41 Single 28 1 46 100 Family 29 0 21 55 Family 30 0 27 127 Single 31 1 30 143 Single 32 0 55 44 Family 33 1 73 132 Family 34 1 26 107 Single 35 0 27 70 Family
E
F
The manager is concerned about the attrition rate at her gym. She would like to identify the profile of loyal members who retain the membership for at least one year. The accompanying data file contains information on whether the member has been loyal (Loyal=1 if the member stayed at the gym for at least one year, 0 otherwise). Also included are the member's age and income (in $1,000) and whether he/she joined on a single or a family plan.
Click here for the Excel Data File
a. Estimate the logistic regression model using Loyal as the response variable and Age, Income, and Single (equals 1 if on a single plan, 0 otherwise) as the predictor variables. Note: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places.
Predictor Variable Constant Age Income Single
Coefficient
b. Predict the probability of being loyal for a 40- and a 60-year-old member with income of $80,000 and on a single plan. Note: Do not round intermediate calculations and round final answers to 2 decimal places.
40-year-old on a single plan 60-year-old on a single plan
percent Percent