Q1. Performance in Forecasting Quarterly Earnings per Share Number of Mean Forecast Error Standard Deviations of Forecasts (Predicted - Actual) Forecast Errors Analyst A 101 0.05 0.10 Analyst B 121 0.02 0.09 Investment analysts often use earnings per share (EPS) forecasts. One test of forecasting quality is the zero-mean test, which states that optimal forecasts should have a mean fore- casting error of 0. (Forecasting error = Predicted value of variable - actual value of variable.) You have collected data (shown in the table above) for two analysts who cover two different industries: analyst A covers the telecom industry; analyst B covers automotive parts and suppliers. A. With u as the population mean forecasting error, formulate null and alternative hypotheses for a zero-mean test of forecasting quality. B. For analyst A, using both a ttest and a ztest, determine whether to reject the null at the 0.05 and 0.01 levels of significance. C. For analyst B, using both a t-test and a ztest, determine whether to reject the null at the 0.05 and 0.01 levels of signicance. D. reviewing the EPS forecasting performance data for analysts A and B, you want to investigate whether the larger average forecast errors of analyst A are due to chance or to a higher underlying mean value for analyst A. Assume that the forecast errors of both analysts are normally distributed and that the samples are independent