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A data analyst builds a model to estimate the retention time (in months) of customers based on their monthly spend (dollars), while allowing for any

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A data analyst builds a model to estimate the retention time (in months) of customers based on their monthly spend (dollars), while allowing for any differences between males and females. He analysed a dataset and got the following results: Coefficients: Estimate Std. Error t value Pr(>|+1) (Intercept) 0.2199 1. 2175 -0. 181 B.858 Spend 6.7471 1.2831 5.G28 3.760 - BG ... sexmale 0.6726 1.4848 e. 453 0.654 Spend: sexmale -0. 1617 1.4208 -e. 114 9.918 Signif. codes: 0 ....' 0.021 ..". 0.01 .' 0.05 '.' 0.1 * * 1 Residual standard error: 0.6209 on 31 degrees of freedon Multiple R-squared: 0.8185, Adjusted R-squared: 0.8089 F-statistic: 46.59 on 3 and 31 DF, p value: 1.351e-11 Question 1 a. What type of model is this? b. Use this model to predict the average retention time (in months) of i. a male that spends $1 per month: ii. a female that spends $1 per month: Question 2 c. By how much do we expect the actual retention time to differ from our predicted retention time, on average? months

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