STAT TECH IN BUSINESS & ECON LL\AC
18th Edition
ISBN: 9781264720545
Author: Lind
Publisher: MCG
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Chapter 14, Problem 14CE
To determine
Perform a hypothesis test to determine whether any of the independent variable is not equal to zero at 0.05 level of significance.
Explain whether one variable can be deleted from the regression equation.
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i. Write out the regression equation ii. What is the sample size used in this investigation? iii. Determine the values of *, ** and ***, **** iv. Conduct a hypothesis test, at the 5% level of significance, to determine whether ? issignificant. v. What would be the growth of the plant if 4g of fertilizer and 7g of ater was given to itdaily? vi. Carry out an F -test at the 1% significance level to determine whether the model issignificant
. A professor at the University of Alabama was interested in evaluating the relationship between family support and delinquency. Using data collected on 4545 families, the researcher used regression to analyze the relationship. The results are presented below.
Variables Entered/Removeda
Model
Variables Entered
Variables Removed
Method
1
Family supportb
.
Enter
a. Dependent Variable: Delinquency
b. All requested variables entered.
Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.249a
.062
.062
1.59168
a. Predictors: (Constant), Family support
ANOVAa
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
759.204
1
759.204
299.671
<.001b
Residual
11479.107
4531
2.533
Total
12238.311
4532
a. Dependent Variable: Delinquency
b. Predictors: (Constant), Family support…
. A professor at the University of Alabama was interested in evaluating the relationship between family support and delinquency. Using data collected on 4545 families, the researcher used regression to analyze the relationship. The results are presented below.
Variables Entered/Removeda
Model
Variables Entered
Variables Removed
Method
1
Family supportb
.
Enter
a. Dependent Variable: Delinquency
b. All requested variables entered.
Model Summary
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
1
.249a
.062
.062
1.59168
a. Predictors: (Constant), Family support
ANOVAa
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
759.204
1
759.204
299.671
<.001b
Residual
11479.107
4531
2.533
Total
12238.311
4532
a. Dependent Variable: Delinquency
b. Predictors: (Constant), Family support…
Chapter 14 Solutions
STAT TECH IN BUSINESS & ECON LL\AC
Ch. 14 - There are many restaurants in northeastern South...Ch. 14 - Prob. 1ECh. 14 - Thompson Photo Works purchased several new, highly...Ch. 14 - A consulting group was hired by the Human...Ch. 14 - Cellulon, a manufacturer of home insulation, wants...Ch. 14 - Refer to Self-Review 141 on the subject of...Ch. 14 - Prob. 5ECh. 14 - Prob. 6ECh. 14 - Prob. 3SRCh. 14 - Given the following regression output, answer the...
Ch. 14 - The following regression output was obtained from...Ch. 14 - A study by the American Realtors Association...Ch. 14 - The manager of High Point Sofa and Chair, a large...Ch. 14 - Prob. 10ECh. 14 - Prob. 11ECh. 14 - A real estate developer wishes to study the...Ch. 14 - Prob. 13CECh. 14 - Prob. 14CECh. 14 - Prob. 15CECh. 14 - Prob. 16CECh. 14 - The district manager of Jasons, a large discount...Ch. 14 - Suppose that the sales manager of a large...Ch. 14 - The administrator of a new paralegal program at...Ch. 14 - Prob. 20CECh. 14 - Prob. 21CECh. 14 - A regional planner is studying the demographics of...Ch. 14 - Great Plains Distributors, Inc. sells roofing and...Ch. 14 - Prob. 24CECh. 14 - Prob. 25CECh. 14 - Prob. 26CECh. 14 - Prob. 28CECh. 14 - Prob. 29CECh. 14 - The director of special events for Sun City...Ch. 14 - Prob. 31CECh. 14 - Prob. 32CECh. 14 - Prob. 33DACh. 14 - Prob. 34DACh. 14 - Prob. 35DACh. 14 - Prob. 1PCh. 14 - Quick-print firms in a large downtown business...Ch. 14 - The following ANOVA output is given. a. Compute...Ch. 14 - Prob. 1CCh. 14 - Prob. 2CCh. 14 - Prob. 3CCh. 14 - In a scatter diagram, the dependent variable is...Ch. 14 - What level of measurement is required to compute...Ch. 14 - If there is no correlation between two variables,...Ch. 14 - Which of the following values indicates the...Ch. 14 - Under what conditions will the coefficient of...Ch. 14 - Given the following regression equation, = 7 ...Ch. 14 - Given the following regression equation, = 7 ...Ch. 14 - Given the following regression equation, = 7 ...Ch. 14 - Prob. 1.9PTCh. 14 - In a multiple regression equation, what is the...Ch. 14 - Prob. 1.11PTCh. 14 - Prob. 1.12PTCh. 14 - For a dummy variable, such as gender, how many...Ch. 14 - What is the term given to a table that shows all...Ch. 14 - If there is a linear relationship between the...Ch. 14 - Given the following regression analysis output: a....Ch. 14 - Given the following regression analysis output. a....
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- Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4arrow_forwardSarah is the office manager for a group of financial advisors who provide financial services for individual clients. She would like to investigate whether a relationship exists between the number of presentations made to prospective clients in a month and the number of new clients per month. The following table shows the number of presentations and corresponding new clients for a random sample of six employees. Employee Presentations New Clients 1 7 2 2 9 3 3 9 4 4 10 3 5 11 5 6 12 3 Sarah would like to use simple regression analysis to estimate the number of new clients per month based on the number of presentations made by the employee per month. The expected number of new clients per month for an employee who made 10 presentations per month is ________. 2.3982 1.6753 3.0521 3.4348arrow_forwardThe statistic used to test whether individual regression coefficients are different from zero in the population is: Select one: a. F O b. b Oc. R2 O d. t Clear my choicearrow_forward
- Suppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The correlation coefficient is 0.941 and the least squares regression line is y = 0.244x + 10.794. Complete parts a and b below. Height, x Head Circumference, y 27.00 25.75 26.25 17.3 25.75 27.50 17.5 26.25 17.1 26.00 27.00 17.4 17.4 17.1 17.1 17.1 (a) Compute the coefficient of determination, R?. R2 =% (Round to one decimal place as needed.) (b) Interpret the coefficient of determination. % of the variation in height is explained by the least-squares regression model. (Round to one decimal place as needed.)arrow_forwardYou have created a line of best fit for your scatterplot. The dots that fall above the regression line have been . . . a.) underestimated by the line b.) overestimated by the line c.) properly estimated by the line Residuals are also called a.) deviations b.) differences between the observed score and the predicted value c.) all of the choices are correct In a regression the x variable is the _______ and the y variable is the _________. a.) criterion, predictor b.) dependent variable, independent variable c.) independent variable, dependent variable d.) predictor, criterionarrow_forwardThe options for part b are: head circumference or heightarrow_forward
- A Math teacher wishes to determine if the number of absences a student incurs correlates with his or her general weighted average. She chose a sample of 7 students and then surveyed their GWA and number of absences. 5 7 Number of Absences (x) GWA (y) 9 10 97.8 90.2 86.4 87.3 85.4 84.5 78.2 Find the equation of the regression line and predict the GWA of a student who incurred 6 absencesarrow_forwardSuppose a doctor measures the height, x, and head circumference, y, of 8 children and obtains the data below. The correlation coefficient is 0.885 and the least squares regression line is y = 0.151x+ 13.311. Complete parts (a) and (b) below. Height, x Head Circumference, y 17.5 17.1 17.3 17.0 17.5 17.4 17.2 17.3 17.4 17.4 17.3 27 25 26 25 28 26.75 26.25 26.75 26.75 27.25 27.25 a ... (a) Compute the coefficient of determination, R?. R =% (Round to one decimal place as needed.) !!arrow_forwardDo a simple linear regression. Determine the descriptive statistics (the coefficients of the sample linear regression line – b0 and b1 – as well as r and r2. Please include the appropriate graphs, calculations, ANOVA table, tests of hypotheses, and interval estimates. Use a hypothetical state with 700 (million dollars) in claims to do the interval estimates. Please interpret the results.arrow_forward
- 2. A study on the factor that determine sales (y in millions of dollars) for a big grocery store chain. The factors considered are advertising expenditures (x) in thousands of dollars), and number of salespeople (x2). The following is part of the results: ANOVA Source Regression df SS MS 2 2956.064 Error 15 736.012 a. What has been the sample size for this regression analysis? b. At a = 05, test to determine if the model is significant. That is, determine if there exists a significant relationship between the independent variables and the dependent variable. c. Determine the multiple coefficient of determination R². d. Determine the adjusted multiple coefficient of determination (adjusted R?).arrow_forwardA real estate builder wishes to determine how house size (House) is influenced by family income (Income) and family size (Size). House size is measured in meter square and income is measured in IDR millions. The builder randomly selected 50 families and ran the multiple regression. Partial Microsoft Excel output is provided below: Regression Statistics Multiple R 0.8479 R Square 0.7189 Adjusted R Square 0.7069 Standard Error 17.5571 Observations 50 ANOVA df SS MS F Significance F Regression 370443.3236 18521.662 0.0000 Residual 14487.7627 308.2503 Total 49 51531.0863 Coefficients Standard Error t Stat P-value Intercept -5.5146 7.2273 -0.763 0.4493 Income 0.4262 0.0392 10.8668 0.0000 Size 5.5437 1.6949 3.2708 0.00020 a. What is the population model of this regression problem?b. What is the sample estimates of the regression problem?c. Which of the independent variables in the model are significant at the 5% level?…arrow_forwardAs part of an effort to induce the public to conserve energy, a researcher wanted to analyze the factors that determine home heating costs. In a city known for its long, cold winters the researcher took a random sample of 35 houses and collected data on the following variables: cost of heating during the month of January, house size in hundreds of square feet, number of windows, and number of occupants per house. A multiple regression model for the cost of heating was estimated with the Excel output shown below: SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept Size Windows Occupants 0.554 0.511 34.898 35 Df 31 34 Coefficients 11.088 5.632 3.179 15.431 SS 46919 37754 84673 Standard Error 4.532 1.489 1.966 6.850 MS 15639.7 1217.9 t Stat 2.45 3.78 1.62 2.25 F 12.84 P-value 0.0202 0.0006 0.1154 0.0316 Significance F 0.000 a. Using a 5% significance level, determine if there exists a significant…arrow_forward
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