A data scientist has access to 1 million observations. He develops and subsequently tests a predictive model of churn. ("Churn" refers to customers who are likely to switch from one service provider to another). The data scientist codes the binary outcomes as (yes churn = 1, no churn =0) on a training set composed of 800,000 observations and a test set composed of 200,000 observations. The Logistic Regression model he estimates is of the form: ln (Odds of Churn) = - 4.80 + 1.50 (Last_Month_Calls_Customer_Care) One of the customers in the database has made 3 calls to customer care in the last month. What is the customer's estimated probability of churn