Final answer:
Predictors for logistic regression to predict customer churn could include demographic information, purchase frequency, behavioral patterns, or all of them, depending on their correlation with churn. These predictors should be selected using data analysis and model selection techniques. The correct option is d) All of the above
Step-by-step explanation:
To calculate the accuracy of using logistic regression for predicting customer churn in 2014 based on purchase behavior before 2013, it is essential to choose the most predictive variables.
The predictors one would use could include a) Demographic information, b) Purchase frequency, c) Behavioral patterns, or d) All of the above, depending on how strongly they correlate with customer churn.
In practice, the choice of predictors would be informed by exploratory data analysis and model selection techniques such as stepwise regression, where variables would be included or excluded based on their statistical significance and contribution to the model's predictive power.
Once the model is fitted with the chosen predictors, its accuracy can be evaluated by comparing the predicted outcomes with the actual churn occurrences in 2014.
The correct option is d) All of the above