QUESTION 7 If the estimate being tested is less than the benchmark, you should conduct a sample hypothesis test. one- two tail right tail left tail no tail All of the choices above None of the choices QUESTION 8 If the estimate is 29 and the benchmark is 28, because of the probability that the estimate suffers from some random sampling error, it would be logical to ask probably due to random sampling error? or is the difference is the estimate probably greater than the benchmark is the estimate greater than the benchmark is the benchmark wrong is alpha too low All of the choices above None of the choices

QUESTION 7 If the estimate being tested is less than the benchmark, you should conduct a sample hypothesis test. one- two tail right tail left tail no tail All of the choices above None of the choices QUESTION 8 If the estimate is 29 and the benchmark is 28, because of the probability that the estimate suffers from some random sampling error, it would be logical to ask probably due to random sampling error? or is the difference is the estimate probably greater than the benchmark is the estimate greater than the benchmark is the benchmark wrong is alpha too low All of the choices above None of the choices

Practical Management Science

6th Edition

ISBN:9781337406659

Author:WINSTON, Wayne L.

Publisher:WINSTON, Wayne L.

Chapter14: Data Mining

Section14.2: Classification Methods

Problem 3P

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The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?
The Baker Company wants to develop a budget to predict how overhead costs vary with activity levels. Management is trying to decide whether direct labor hours (DLH) or units produced is the better measure of activity for the firm. Monthly data for the preceding 24 months appear in the file P13_40.xlsx. Use regression analysis to determine which measure, DLH or Units (or both), should be used for the budget. How would the regression equation be used to obtain the budget for the firms overhead costs?
page 4 of 19) - Google Chrome squ.edu.om/mod/quiz/attempt.php?attempt3D1245076&cmid%3663426&page%3D3 earning System (Academic) erations Management || fall20 Quiz stion 4 Mean Absolute Deviation (MAD) is the always the best in assessing a forecast model accuracy yet vered Select one: ked out of O a. True O b. False Hajir lag question 13 Next page 10 19
8. assignment variable at which the treatment status does NOT change In Regression Discontinuity framework, the cutoff is defined as the level of the True False 9. What regression equation do we use for regression discontinuity framework? a) Y = Bo + B1 T + B2Xu+ Ei b) Y = Bo + B,T+ B2C + ei c) Y, = Bo + B, T+ B2 (Xi-C) + ei d) Y, = Bo + B1T + B2 (Xu + C) + € 10. Regression Discontinuity Design accomplices apples-to-apples comparison by comparing individuals as far from the cutoff as possible. True False
Which best describes the null hypothesis associated with an Analysis of Variance (ANOVA)? Group of answer choices a. Ho: Variance 1 = Variance 2 = Variance 3 b. Ho: Standard Deviation 1 = Standard Deviation 2 = Standard Deviation 3 c. Ho: Proportion 1 = Proportion 2 = Proportion 3 d. Ho: Median 1 = Median 2 = Median 3 e. Ho: Mean 1 = Mean 2 = Mean 3
(a) Assuming that a simple linear regression model is appropriate, obtain the least squares fit relating selling price to taxes paid. What is the estimate of o²? (b) Find the mean selling price given that the taxes paid are x = 7.50. (c) Calculate the fitted value of y corresponding to x = 5.8980. Find the corresponding residual.
8. Suppose the population is normally distributed. Specify the appropriate hypothesis test and determine the appropriate critical z or t point(s) for each of the following tests concerning the population mean : (a) upper-tailed test: a - 0.025, n - 25,_ - 3.0. (b) lower-tailed test: a - 0.05, n - 30, s - 9.0. (c) two-tailed test: a - 0.02, n - 5I, s - 6.5. (d) two-tailed test: a - 0.10, n - 36, - 3.8.
Consider the ANOVA table that follows. Analysis of Variance Source DF SS MS F p Regression 2 77.907 38.954 4.14 0.021 Residual Error 62 583.693 9.414 Total 64 661.600 a-1. Determine the standard error of estimate. (Round your answer to 3 decimal places.) a-2. About 95% of the residuals will be between what two values? (Round your answers to 3 decimal places.) b-1. Determine the coefficient of multiple determination. (Round your answer to 3 decimal places.) b-2. Interpret the coefficient of multiple determination. (Round your answer to 1 decimal place.) Determine the coefficient of multiple determination, adjusted for the degrees of freedom. (Round your answer to 3 decimal places.) Prev Question 5 of 30 Total5 of 3
6. List and explain in detail why we include disturbance term or error term in the model?
General Motors would like an estimate of the chance that Tesla will bring the cost of batteries down from $300 per kWh to $70. Dr. Tetlock has developed a process whereby selected teams are better estimators of future probabilities than experts, General Motors is willing to pay Dr. Tetlock for his teams' O scenarios O contingency plans O forecasts
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Bo Using data from 50 workers, a researcher estimates Wage = ẞe + B₁Education + B2Experience + B3Age + ε, where Wage is the hourly wage rate and Education, Experience, and Age are the years of higher education, the years of experience, and the age of the worker, respectively. A portion of the regression results is shown in the following table. Intercept Education Experience Age Coefficients Standard Error t Stat p-Value 7.17 4.26 1.68 0.0991 1.81 0.35 5.17 0.0000 0.45 0.10 4.50 0.0000 -0.01 0.06 -0.17 0.8684 a-1. Interpret the point estimate for ẞ1. As Education increases by 1 year, Wage is predicted to increase by 1.81/hour. As Education increases by 1 year, Wage is predicted to increase by 0.45/hour. As Education increases by 1 year, Wage is predicted to increase by 1.81/hour, holding Age and Experience constant. As Education increases by 1 year, Wage is predicted to increase by 0.45/hour, holding Age and Experience constant. a-2. Interpret the point estimate for $2. As Experience…