Question #111

of 139 Jacob Warner, CFA, is evaluating a regression analysis recently published in a trade journal that hypothesizes that the annual performance of the S&P 500 stock index can be explained by movements in the Federal Funds rate and the U.S. Producer Price Index (PPI). Which of the following statements regarding his analysis is most accurate? A) If the p-value of a variable is less than the significance level, the null hypothesis cannot be rejected. B) If the t-value of a variable is less than the significance level, the null hypothesis should be rejected. C) If the p-value of a variable is less than the significance level, the null hypothesis can be rejected. A real estate agent wants to develop a model to predict the selling price of a home. The agent believes that the most important variables in determining the price of a house are its size (in square feet) and the number of bedrooms. Accordingly, he takes a random sample of 32 homes that has recently been sold. The results of the regression are: Coefficient Standard Error t-statistics Intercept 66,500 59,292 1.12 House Size 74.30 21.11 3.52 Number of Bedrooms 10306 3230 3.19 R2 = 0.56; F = 40.73 Selected F- table values for significance level of 0.05: 1 2 28 4.20 3.34 29 4.18 3.33 30 4.17 3.32 32 4.15 3.29 (Degrees of freedom for the numerator in columns; Degrees of freedom for the denominator in rows) Additional information regarding this multiple regression: 1. Variance of error is not constant across the 32 observations. 2. The two variables (size of the house and the number of bedrooms) are highly correlated. 3. The error variance is not correlated with the size of the house nor with the number of bedrooms.