You work for a life insurance company and are preparing for a briefing of the board. Your economic tells you that the best predictor of life insurance (lins) holdings is income. You gather the relevant data (family life insurance and family income, both in thousands of dollars) and want to analyze it, running a regression of life insurance holdings on income. The output, as well as some other statistics, follow. You need to interpret the regression results, and as the board has not benefited from taken this course, you need to describe in words what is going on. Explain what the following mean that is. don't just give the numbers, interpret what they mean for the problem). Coefficient on the constant. Coefficient on income. The value beta_0 + beta_1 for some arbitrary x_0. The value for R^2 You also need to think about the population regression line Write down the population regression function. What are the population error terms likely to be (that is. what causes deviations from the population mean)? Under certain assumptions the coefficient estimates are unbiased. Describe what the property of unbiasedness is in terms of the above regression line, and explain what this means for the chance that your estimates in this particular sample are close to the true values. What assumptions are required on the population model for the estimates to be unbiased? Do you think that they hold here? Make an argument one way or the other