In the churn dataset, there is a variable named Monthly_Rate, which represents the amount the customer pays for service each month and takes on numeric values. A logistic regression model is fit to the data to predict if a customer will churn (Y = 1). The fitted coefficient (slope) value for Monthly_Rate is -1.2. Pickles wants to understand what this means. What should you tell him?

Based on the model, higher monthly rates are associated with lower probability of churn.

Based on the model, lower monthly rates are associated with higher probability of churn.

Based on the model, lower monthly rates are associated with lower probability of churn.

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