Questions Answer the questions below using the data in the AnalystData spreadsheet. The various tabs of the spreadsheet sort the data in different ways to facilitate calculations for these questions. 1. Calculate a 95% confidence interval for the proportion of forecast errors that are positive. Comment. 2. Calculate a 95% confidence interval for mean forecast error for transportation companies. Calculate a 95% confidence interval for technology companies. Calculate a 95% confidence interval for the difference between the two means. 3. Did forecast accuracy change from the 1980s to the 1990s? Execute a hypothesis test to compare the mean errors in the two decades. Clearly state the hypotheses and the conclusion. 4. Are forecasts based on more analysts more or less accurate than those based on fewer analysts? Carry out a hypothesis test to compare forecasts based on 20 or fewer analysts with forecasts based on more than 20 analysts. 5. There are 37 forecasts (same company, same period) for which our data includes specific forecasts submitted by Goldman Sachs and by Credit Suisse First Boston. Find the mean forecast error for each of these two brokerage houses. Use a matched pairs hypothesis test to determine whether the difference is statistically significant. 6. Give two distinct reasons why assumptions underlying the techniques you used in answering one or more of the questions above may be violated. Be specific. Analyzing the Analysts Page 4