Statistics for Management and Economics (Book Only)
11th Edition
ISBN: 9781337296946
Author: Gerald Keller
Publisher: Cengage Learning
expand_more
expand_more
format_list_bulleted
Question
Chapter 18.2, Problem 31E
a:
To determine
Creating indicators.
b:
To determine
Testing the new hypothesis.
Expert Solution & Answer
Want to see the full answer?
Check out a sample textbook solutionStudents have asked these similar questions
Sherwin-Williams Company is attempting to develop a demand model for its line of exterior house paints. The company’s chief economist feels that the most important variable affecting paint sales (Q) (measured in gallons) is the Selling price (P) (measured in Ghana cedis per gallon). The chief economist decides to collect data on the variables in a sample of 10 company sales regions that are roughly equal in population. Data on paint sales, and selling prices were obtained from the company’s marketing department. The data are shown in the table below:
Sherwin-Williams Company Data
Sales Region
Sales (Q)
Selling Price (P) (GHS/Gallon)
1
160
15
2
220
13.5
3
140
16.5
4
190
14.5
5
130
17
6
160
16
7
200
13
8
150
18
9
210
12
10
190
15.5
Specify the linear demand model for Sherwin-William’s paint.
Estimate the demand…
What are the various Standard errors in direct multiperiod regressions?
You have been presented with the following data and asked to fit statistical demand functions:
PERIOD
QUANTITY
PRICE
INCOME
ADVERTISING
1
120
8.00
10
3
2
165
4.00
22
7
3
120
7.00
20
5
4
165
3.00
20
8
5
180
4.00
30
8
6
90
10.00
19
6
7
150
4.00
18
10.2
8
190
1.60
25
9.3
9
160
5.00
30
8
10
200
2.00
35
9.5
Linear Relationship
Use any multiple regression packages to estimate a linear relationship between the dependent variable and the independent variables.
Is the estimated demand function “good”? Why or why not?
Discuss the economic implications of the various coefficients.
Non-linear relationship.
Select and estimate any form of non-linear relationship.
Is the estimated demand function “good”? Why or why not? Compare with the linear form above. Elaborate
Chapter 18 Solutions
Statistics for Management and Economics (Book Only)
Ch. 18.1 - Prob. 1ECh. 18.1 - Prob. 2ECh. 18.1 - Prob. 3ECh. 18.1 - Prob. 4ECh. 18.1 - Prob. 5ECh. 18.1 - Prob. 6ECh. 18.1 - Prob. 7ECh. 18.1 - Prob. 8ECh. 18.1 - Prob. 9ECh. 18.1 - Prob. 10E
Ch. 18.2 - Prob. 11ECh. 18.2 - Prob. 12ECh. 18.2 - Prob. 13ECh. 18.2 - Prob. 14ECh. 18.2 - Prob. 15ECh. 18.2 - Prob. 16ECh. 18.2 - Prob. 17ECh. 18.2 - Prob. 18ECh. 18.2 - Prob. 19ECh. 18.2 - Prob. 20ECh. 18.2 - Prob. 21ECh. 18.2 - Prob. 22ECh. 18.2 - Prob. 23ECh. 18.2 - Prob. 24ECh. 18.2 - Prob. 25ECh. 18.2 - Prob. 26ECh. 18.2 - Prob. 27ECh. 18.2 - Prob. 28ECh. 18.2 - Prob. 29ECh. 18.2 - Prob. 30ECh. 18.2 - Prob. 31ECh. 18.2 - Prob. 32ECh. 18.2 - Prob. 33ECh. 18.3 - Prob. 34ECh. 18.3 - Prob. 35ECh. 18.3 - Prob. 36ECh. 18.3 - Prob. 37ECh. 18.4 - Prob. 38ECh. 18.4 - Prob. 39ECh. 18.4 - Prob. 40ECh. 18.4 - Prob. 41ECh. 18.4 - Prob. 42ECh. 18 - Prob. 43CECh. 18 - Prob. 44CECh. 18 - Prob. 45CECh. 18 - Prob. 46CECh. 18 - Prob. 47CECh. 18 - Prob. 48CECh. 18 - Prob. 49CE
Knowledge Booster
Similar questions
- In multiple OLS regressions, if you are using power terms to fit for nonlinearity, how do you interpret the coefficients? For example: Yi=B1+B2X+B3X^2+Ui and B2 and B3 are both significant.arrow_forwardQ.3. A random sample of ten families had the following income and food expenditure Families A B C D E F G H I J Income 18 28 31 38 15 13 24 36 33 40 Food Expenditure 7 10 8 10 6 4 7 10 9 10 Estimate the regression line of food expenditure on income.arrow_forward(Don't accept answers from Chat-GPT)You are estimating the following simple linear regression model: Edui = B0 + B1 MomEdu + ui. Where Edu is the years of schooling of an individual and MomEdu is the years of education of the individual's mother (Note: We might estimate this sort of regression to learn about intergenerational transmission of economic success.) a. Suppose you restrict your sample to individuals with MomEdui = 10 What happens to the OLS estimates? b. Suppose you have two random samples of size 100, both with the same In the first sample, half of the mothers have 12 yearsof education and half have 14 years of education. In the second sample, one quarter of of the mothers have each of 10, 12, 14. and 16 years of education. Does the variance of the OLS estimator differ between the two samples? Explain why or why not. C. Suppose you estimate the above regression using a random sample of 100 observations. Then you find another random sample of 100 with the same as the…arrow_forward
- The appropriate statistic to examine the goodness of fit of a two-variable regression model is _____. Select one: a. t-statistic b. F-statistic c. R2-statistic d. Chi-square statisticarrow_forwardA finance manager employed by an automobile dealership believes that the number of cars sold in his local market can be predicted by the interest rate charged for a loan. Interest Rate (%) Number of Cars Sold (100s) 3 10 5 7 6 5 8 2 The finance manager performed a regression analysis of the number of cars sold and interest rates using the sample of data above. Shown below is a portion of the regression output. Regression Statistics Multiple R 0.998868 R2 0.997738 Coefficient Intercept 14.88462 Interest Rate -1.61538 2. Is interest rate charged for a loan the most important factor to be considered in predicting future car sales? Explain reasoning.The dealership's vice-president of marketing has requested a sales forecast at the prevailing interest rate of 7%. 3. As finance manager, what reasons would you convey to the vice-president in recommending this forecasting model? 4. Is the prediction of car sales…arrow_forwardA finance manager employed by an automobile dealership believes that the number of cars sold in his local market can be predicted by the interest rate charged for a loan. Interest Rate (%) Number of Cars Sold (100s) 3 10 5 7 6 5 8 2 The finance manager performed a regression analysis of the number of cars sold and interest rates using the sample of data above. Shown below is a portion of the regression output. Regression Statistics Multiple R 0.998868 R2 0.997738 Coefficient Intercept 14.88462 Interest Rate -1.61538 1. Are there factors other than interest rate charged for a loan that the finance manager should consider in predicting future car sales? 2. Is interest rate charged for a loan the most important factor to be considered in predicting future car sales? Explain reasoning.The dealership's vice-president of marketing has requested a sales forecast at the prevailing interest rate of 7%. 3. As…arrow_forward
- Using the regression results in column (1):a. Is the college–high school earnings difference estimated from thisregression statistically significant at the 5% level? Construct a 95%confidence interval of the difference.b. Is the male–female earnings difference estimated from this regressionstatistically significant at the 5% level? Construct a 95% confidenceinterval for the differenc(answer for me part please)arrow_forwardSuppose you examined blood of 36 patients with the aim to study the relation between sugar level in blood (in mg/dL) and the amount of artificial sweetener (measured in grams). Your regression shows: blood=7.1 + 0.4*sweatener - 0.2*female. a)What is the most precide interpretation of the estimated coefficient for sweetener? b)What is the most precide interpretation of the estimated coefficient for the constant?arrow_forwardA student used multiple regression analysis to study how family spending (y) is influenced by income (x1), family size (x2), and additions to savings (x3). The variables y, x1, and x3 are measured in thousands of dollars. The following results were obtained. ANOVA df SS Regression 3 45.9634 Residual 11 2.6218 Total Coefficients Standard Error Intercept 0.0136 x1 0.7992 0.074 x2 0.2280 0.190 x3 -0.5796 0.920 A) Carry out a test to see if x3 and y are significantly related. Use a 5% level of significance.arrow_forward
- How is imperfect collinearity of regressors different from perfect collinearity?Compare the solutions for these two concerns with multiple regressionestimation.arrow_forwardSuppose you examined blood of 36 patients with the aim to study the relation between sugar level in blood (in mg/dL) and the amount of artificial sweetener (measured in grams). Your regression shows: blood=7.1 + 0.4*sweatener - 0.2*female. What is the most precide interpretation of the estimated coefficient for sweetener?arrow_forwardWhat do you mean by Confidence Sets for Multiple Coefficients? How to construct a confidence set for two or more regression coefficients?arrow_forward
arrow_back_ios
SEE MORE QUESTIONS
arrow_forward_ios
Recommended textbooks for you
- Managerial Economics: Applications, Strategies an...EconomicsISBN:9781305506381Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. HarrisPublisher:Cengage Learning
Managerial Economics: Applications, Strategies an...
Economics
ISBN:9781305506381
Author:James R. McGuigan, R. Charles Moyer, Frederick H.deB. Harris
Publisher:Cengage Learning