Oncologists wanted to know the effect of sex (male, female) on age at diagnosis of colorectal cancer. They extracted a random sample of 30 medical charts of colorectal cancer patients and recorded the sex and age of each patient. These oncologists collaborated with a statistician to fit a simple linear regression model to these data. 1. Name the variables in this model ? [0.2 point] 2. For each variable, say what type of variable it is (for example, categorical or continuous). [0.2 point] 3. Using notations (such as Y for outcome, X1 for predictor, beta0, beta1 etc for slope, intercept etc), write down the regression model, defining all terms. [0.6 point] 4. Suppose the statistician uses the following code for sex in the regression model: X1 = 1 for males and X1 = 0 for females. Suppose the intercept is estimated to be 60 and the slope of the regression is estimated to be 5. Interpret the slope. [0.5 point] 5. Suppose the statistician fits a linear regression to the data extracted by these oncologists and wants to test whether the association between sex and age at diagnosis of colorectal cancer is 0. o What is the sampling distribution of