Search
Info
Warning
Danger

Study Resources (Statistics)

THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: An actuary wanted to develop a model to predict how long individuals will live. After consulting a number of physicians, she collected the age at death (y), the average number of hours of exercise per week (x1), the cholesterol level (x2), and.
12 Views
View Answer
    81) During the coefficient estimation stage of the model-building exercise, only the point estimates should be obtained for the multiple regression model.   82) If dummy variables are used to represent distinct subsets or regions, then a linear relationship between predictor variables will result, and estimation of coefficients will be impossible.   83) Dummy.
12 Views
View Answer
113) What problems can occur when the independent variables are correlated with each other?   114) Explain what is meant by specification bias. What effects does specification bias have on the results of a regression?   115) Write the model specification and define the variables for a multiple regression model to predict earnings as.
12 Views
View Answer
    91) What is the value of ? A) 0.021 B) 0.017 C) 1.183 D) 1.282 92) Determine the value of . A) 0.2523 B) 1.433 C) 0.1761 D) 0.202   93) The value of is: A) -0.0000699 B) 0.0002585 C) 0.796 D) -0.27   94) Determine SSR. A) 3.00 B) 0.049 C) 0.016 D) 9.26   95) Which of the following is the value of SSE? A) 6.00 B) 0.0018 C) 0.011 D) 9.26 96) What is.
1 Views
View Answer
    101) For a particular regression, the adjusted coefficient of determination, 2 can never be larger than the coefficient of determination, R2.   102) The test on all parameters of a regression model has the following null and alternative hypotheses: H0 : β1 = β2 = β3 = ? ? ? ? ?.
1 Views
View Answer
THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: An actuary wanted to develop a model to predict how long individuals will live. After consulting a number of physicians, she collected the age at death (y), the average number of hours of exercise per week (x1), the cholesterol level (x2), and.
12 Views
View Answer
THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: The director of a local tourist board is interested in determining the factors that influence the hotel occupancy rate in his city each month. Hotel occupancy can be measured as the percentage of available hotel rooms that are occupied by paying customers..
12 Views
View Answer
    91) If redundant predictor variables are correlated with other predictor variables, the variance of the coefficient estimates for the important variables will be decreased.   92) In many time-series applications, the dependent variable in a time period is often related to the value taken by this variable in the previous time period..
12 Views
View Answer
    71) In a multiple regression analysis, six independent variables are used in the equation based on a sample of 45 observations.  What are the degrees of freedom associated with the F statistic? A) 6 and 45 B) 5 and 44 C) 6 and 38 D) 4 and 40   72) In a multiple regression model, there.
11 Views
View Answer
THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: Suppose we estimate the regression Yt = β0 + β1x1t + β2x2t + β3x3t + β4x4t + εt using 36 months of data.   125) From the regression results we calculate a Durbin-Watson test statistic of 1.03. What can we conclude about the possibility.
12 Views
View Answer
119) Explain what is meant by multicollinearity. What effects does multicollinearity have on the results of regression coefficients? 120) You are interested in examining the factors that determine the average length of stay by patients in hospitals across states. You collect data on the following variables: Y = statewide average hospital stay X1.
11 Views
View Answer
THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: Suppose we estimate the regression Yt = β0 + β1x1t + β2x2t + β3x3t + β4x4t + εt using 36 months of data.   128) From the regression results we calculate a Durbin-Watson test statistic of 2.68. What can we conclude about the possibility.
12 Views
View Answer
    111) In a multiple regression model with K independent variables on n observations, the standard error of the estimate is = .   112) In multiple regression analysis, the mean square regression (MSR) is a measure of the explained variability adjusted for the number of independent variables.   113) The multiple coefficient of.
1 Views
View Answer
THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: The computer output for the multiple regression model, y = β0 + β1X1 + β2X2 + ε is shown below. However, because of a printer malfunction some of the results are not shown. These are identified by asterisks.   Predictor Coefficients Standard Error t Constant * 6.15 4.11 x1 3.51 * 1.25 x2 -0.71 0.30 *   S = *R-Sq =.
12 Views
View Answer
THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: As director of the local tourist board, you are interested in determining the factors that influence the hotel occupancy rate in your city each month. Hotel occupancy can be measured as the percentage of available hotel rooms that are occupied by paying.
1 Views
View Answer
    101) The range of the values of the Durbin-Watson statistic d is 0 ≤ d ≤ 4.   102) If the random errors in a model are independent, then the estimated standard errors for the coefficients are biased.   103) In regression equations, involving several independent variables, the multicollinearity problem arises from patterns.
12 Views
View Answer
    21) What is the 95% confidence interval for β1? A) 2.13 ± 4.17 B) 4.59 ± 4.38 C) 2.13 ± 4.38 D) 4.59 ± 4.17 22) In multiple regression analysis, the ratio MSR/ yields the: A) F-test statistic for testing the validity of the regression equation. B) t-test statistic for testing each individual regression coefficient. C) multiple coefficient.
12 Views
View Answer
THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: As director of the local tourist board, you are interested in determining the factors that influence the hotel occupancy rate in your city each month. Hotel occupancy can be measured as the percentage of available hotel rooms that are occupied by paying.
1 Views
View Answer
THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: A regression analysis has produced the following partial analysis of variance table:   Analysis of Variance Source SS df MS Regression 2,160 4   Residual Error 750 30     213) Compute and se.   214) Compute SST.   215) Compute the proportion of the total sample variability that is explained by the regression.   216) Compute the adjusted coefficient of determination. 217) Compute the.
12 Views
View Answer
THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: Consider the following regression model: Y = β0 + β1X1 + β2X2 + β3X3 + ε. Suppose that you have estimated the coefficients for the model, and obtained the partial ANOVA table shown below.   Analysis of Variance Source df SS MS F-ratio Regression 3 3,900 * * Residual Error 31 3,720 *     228) Complete the missing values identified.
12 Views
View Answer
THE NEXT QUESTIONS ARE BASED ON THE FOLLOWING INFORMATION: The computer output for the multiple regression model, y = β0 + β1X1 + β2X2 + ε is shown below. However, because of a printer malfunction some of the results are not shown. These are identified by asterisks.   Predictor Coefficients Standard Error t Constant * 6.15 4.11 x1 3.51 * 1.25 x2 -0.71 0.30 *   S = *R-Sq =.
12 Views
View Answer
233) Adjusting the coefficient of determination is considered particularly important in multiple regression situations. Why? 234) The t statistic and the partial F statistic are closely related. Explain this relationship. Which would you prefer to use?   235) Consider the following statistics of a multiple regression model: n = 25, K = 5,.
11 Views
View Answer
    131) A multiple regression analysis that includes 25 data points and 4 independent variables produces SST = 400 and SSR = 300. The multiple standard error of the estimate for the analysis is 5. 132) Adding independent variables to the multiple regression model increases the value of the coefficient of determination.   133).
1 Views
View Answer
  1) If the Durbin-Watson statistic has a value close to 0 or 4, which assumption is violated? A) normality of the errors B) independence of errors C) homoscedasticity D) variance of errors   2) Suppose the following scatter plot shows the relationship between X and Y. How might you model Y?     A) with dummy variables B) with the.
14 Views
View Answer