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 forecasting 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 μ as the populations mean forecasting error, formulate null and alternative hypotheses for a zero-mean test of forecasting quality.

B. For Analyst A, using both a t-test and a z-test, 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 z-test, determine whether to reject the null at the 0.05 and 0.01 levels of significance.

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Performance in Forecasting Quarterly Earnings per Share Mean Forecast Error (Predicted – Actual) 0.05 Number of Forecasts Standard Deviations of Forecast Errors Analyst A Analyst B 0.10 101 0.09 op2 121