Question 6: Regression (2+2+2+2+2 marks) This question uses the car insurance example described on page 3. The output below comes from running a linear regression in the R statistical environment where the response (dependent) variable was claim and the predictors consisted of each of the other variables as well as the square of age Call : Im (formula = claim ~ female + age + agesq + lowSES + turbo, date = car . insurance Residuals : Min 10 Median 30 Max -0. 55245 -0.25519 -0.15786 -0.05717 0. 94351 Coefficients : Estimate Std. Error t value Pr ()[t/ } (Intercept) 4.751e-01 4. 692e-02 10.126 Female -1. 421e-01 1.141e-02 -12.446