Y-1.04 +0.24X₁-0.27X2whereY = quarterly sales (in thousands of cases) of the cold remedyX₁ = Cascade's quarterly advertising (x $1,000) for the cold remedyX₂= competitors' advertising for similar products (x $10,000)Here is additional information concerning the regression model:8b1 = 0.052, 862 = 0.080, R² = 0.640, 8e-1.63, F-statistic=31.402, and Durbin-Watson (d) statistic=0.499.Which of the independent variables (if any) appears to be statistically significant (at the 0.05 level) in explaining sales of theremedy? (Hint: to.05/2,33-32.042.) Check all that apply.□ X₁OX2What proportion of the total variation in sales is explained by the regression equation?0.6400.080O 0.132O 0.052The given F-value shows that youreject the null hypothesis that neither of the independent variables explains asignificant (at the 0.05 level) proportion of the variation in income. (Hint: Fo.05,2,33-2-F3.316.) whereY = quarterly sales (in thousands of cases) of the cold remedyX₁ Cascade's quarterly advertising (x $1,000) for the cold remedyX2 competitors' advertising for similar products (x $10,000)=Here is additional information concerning the regression model:$61 0.052, 862=0.080, R2 = 0.640, 8= 1.63, F-statistic 31.402, and Durbin-Watson (d) statistic = 0.499.-Which of the independent variables (if any) appears to be statistically significant (at the 0.05 level)'in explaining sales of the coldremedy? (Hint: to.05/2,33-3 2.042.) Check all that apply.O X₁X₂What proportion of the total variation in sales is explained by the regression equation?O 0.640O 0.080O 0.1320.052reject the null hypothesis that neither of the independent variables explains aThe given F-value shows that you.sinnificant fat the 0.05 level) proportion of the variation in income. (Hint: Fo.05,2,33-2- 3.316.)

Given The regression equation: Here The standard error of the regression coefficient The slope…

Y = -1.04+0.24X₁-0.27X₂ where Y = quarterly sales (in thousands of cases) of the cold remedy X₁ = Cascade's quarterly advertising (x $1,000) for the cold remedy X₂ = competitors' advertising for similar products (x $10,000) Here is additional information concerning the regression model: 8b1 = 0.052, 862 = 0.080, R² = 0.640, s 1.63, F-statistic = 31.402, and Durbin-Watson (d) statistic = 0.499. Which of the independent variables (if any) appears to be statistically significant (at the 0.05 level) in explaining sales of the remedy? (Hint: to.05/2,33-2.042.) Check all that apply. O X₁ OX₂ What proportion of the total variation in sales is explained by the regression equation? O 0.640 O 0.080 O 0.132 O 0.052 The given F-value shows that you reject the null hypothesis that neither of the independent variables explains a significant (at the 0.05 level) proportion of the variation in income. (Hint: F0.05,2,33-2-F3.316.)

Y = -1.04+0.24X₁-0.27X₂ where Y = quarterly sales (in thousands of cases) of the cold remedy X₁ = Cascade's quarterly advertising (x $1,000) for the cold remedy X₂ = competitors' advertising for similar products (x $10,000) Here is additional information concerning the regression model: 8b1 = 0.052, 862 = 0.080, R² = 0.640, s 1.63, F-statistic = 31.402, and Durbin-Watson (d) statistic = 0.499. Which of the independent variables (if any) appears to be statistically significant (at the 0.05 level) in explaining sales of the remedy? (Hint: to.05/2,33-2.042.) Check all that apply. O X₁ OX₂ What proportion of the total variation in sales is explained by the regression equation? O 0.640 O 0.080 O 0.132 O 0.052 The given F-value shows that you reject the null hypothesis that neither of the independent variables explains a significant (at the 0.05 level) proportion of the variation in income. (Hint: F0.05,2,33-2-F3.316.)

Managerial Economics: Applications, Strategies and Tactics (MindTap Course List)

14th Edition

ISBN:9781305506381

Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Publisher:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris

Chapter4: Estimating Demand

Section: Chapter Questions

Problem 4E

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Suppose you decide to estimate a student consumption function. After you run an OLS regression on your data set with 36 observations, you obtain the following. The estimated regression, along with standard errors and t-statistics, CO = - 47.143 + 0.9714 YD (se) (2.0307) (0.157) (t) ( ) (6.187) Where, CO : the average annual consumption expenditures of the students on items other than tuition and room. YD : the average annual disposable income (including gifts) of the students Suppose that disposable income is increased by 1000 dollars on average. What would be the predicted consumption expenditures?
Suppose you decide to estimate a student consumption function. After you run an OLS regression on your data set with 36 observations, you obtain the following. The estimated regression, along with standard errors and t-statistics, CO = - 47.143 + 0.9714 YD (se) (2.0307) (0.157) (t) ( ) (6.187) Where, CO : the average annual consumption expenditures of the students on items other than tuition and room. YD : the average annual disposable income (including gifts) of the students a) Interpret the slope and the intercept. b) Compute the test statistics ( t value and critical t ) for the intercept of the regression. Note that significance level is 0.10. c) Suppose that disposable income is increased by 1000 dollars on average. What would be the predicted consumption expenditures?
Suppose the Sherwin-Williams Company has developed the following multiple regression model, with paint sales Y (x 1,000 gallons) as the dependent variable and promotional expenditures A (x $1,000) and selling price P (dollars per gallon) as the independent variables. Y=α+βaA+βpP+εY=α+βaA+βpP+ε Now suppose that the estimate of the model produces following results: α=344.585α=344.585, ba=0.102ba=0.102, bp=−11.192bp=−11.192, sba=0.173sba=0.173, sbp=4.487sbp=4.487, R2=0.813R2=0.813, and F-statistic=11.361F-statistic=11.361. Note that the sample consists of 10 observations. 1.) According to the estimated model, holding all else constant, a $1,000 increase in promotional expenditures decrease or increase sales by approximately 102,813 or 11,192 gallons. Similarly, a $1 increase in the selling price decrease or increase sales by approximately 813,11,192 or 102 gallons. 2.)Which of the independent variables (if any) appears to be statistically significant (at the 0.05…
Refrigerator prices are affected by characteristics such as whether or not the refrigerator is on sale, whether or not it is listed as a Sub- Zero brand, the number of doors (one door or two doors), and the placement of the freezer compartment (top, side, or bottom). The table below shows the regression output from a regression model using the natural log of price as the dependent variable. The model was developed by the Bureau of Labor Statistics. Variable Coefficient Standard Error t Statistic 5.4841 Intercept 0.13081 41.92 Sale price -0.0733 0.0234 -3.13 Sub-Zero brand 1.1196 0.1462 7.66 0.06956 0.005351 13.00 Total capacity (in cubic feet) Two-door, freezer on bottom Two-door, side freezer 0.04657 0.08085 0.58 Two-door, freezer on top 0.03596 -9.55 Base -0.3432 -0.7096 -0.8820 One door with freezer 0.1310 -5.42 -5.92 One door, no freezer 0.1491 (a) Write the regression model, being careful to exclude the base indicator variable. (Negative amounts should be indicated by a minus…
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You are interested in how the number of hours a high school student has to work in an outside job has on their GPA. In your regression you want to control for high school standing and so you run the following regression: GPA = 3.4 0.03 * HrsWrk - 0.7 * Frosh - 0.3 * Soph +0.1 * Junior (1.1) (0.013) (0.23) (0.14) (0.08) where HrsWrk is the number of hours the student works per week, and Frosh, Soph, and Junior are dummy variables for the student's class standing. a) If you include a dummy variable for seniors, that would cause a Hint: type one word in each blank. For the rest of questions, type a number in one decimal place. b) The expected GPA of a Sophomore who works 10 hours per week is c) The expected GPA of a Senior who works 10 hours per week is d) If Dom and Sarah work the same number of hours per week, but Dom is a Junior and Sarah is a Freshman. Dom is expected to have a higher GPA than Sarah. e) Suppose you rewrite the regression as: problem. GPA = ₁HrsWrk + ß2Frosh + B2Soph +…
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XYZ company is interested in quantifying the impact of consumer promotions on the sales of its packaged food product. XYZ has historical data on the following variables for 38 weeks: • Sales: Weekly sales volume in thousands of units.• Prom: Weekly spending on consumer promotions in thousands of Dollars" "A regression analysis was applied to XYZ historical dataset. The dependent variable is weekly Sales and the independent variables are weekly Prom and weekly Lagged Prom (i.e., last week Prom). This is a summary of the regression output:Sales = 0.80 + 1.20*Prom - 0.40*Lag(Prom) • R-squared=0.85• F-Statistic=23.83• p-value=0.001 (for the overall regression)•All regression coefficients are statistically significant at the 5% level." A. What will be the predicted sales volume ? B. What is the gross margin of this net volume impact due to $1000 spending per week on consumer promotions, if brand makes $2.20 gross margin per unit . C. What is the ROI of this promotion? D. What is predicted…
General Cereals is using a regression model to estimate the demand for Tweetie Sweeties, a whistle-shaped, sugar-coated breakfast cereal for children. The following (multiplicative exponential) demand function is being used: QD = 6,280 P(-2.15) A1.75N2.70 where QD = quantity demanded, in 10-oz boxes P = price per box, in dollars A = advertising expenditures on daytime television, in dollars N = proportion of the population under 12 years old, in percent What is the point price elasticity of demand for Tweetie Sweeties? 1.75 -1.23 2.70 -2.15 What is the advertising elasticity of demand? 0.65 1.75 -2.15 2.70 According to the estimated model, a percent increase in the proportion of the population under 12 years old by percent. the quantity demanded
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