STAT TECH IN BUSINESS & ECON AC
18th Edition
ISBN: 9781264731657
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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The agronomist believed that the amount of rainfall as well as the amount of fertilizer used would affect the crop yield. She did the experiment in the following way. Thirty greenhouses were rented. In each, the amount of fertilizer and the amount of water were varied. At the end of the growing season, the amount of corn was recorded. Use ?=0.05
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Chapter 14 Solutions
STAT TECH IN BUSINESS & ECON 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_forwardi. 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 issignificantarrow_forward. 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…arrow_forward
- . 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…arrow_forwardIn a multiple regression analysis, two independent variables are considered, and the sample size is 30. The regression coefficients and the standard errors are as follows. b1 = 1.331 Sb1 = 0.80 b2 = −2.922 Sb2 = 0.64 Conduct a test of hypothesis to determine whether either independent variable has a coefficient equal to zero. Would you consider deleting either variable from the regression equation? Use the 0.05 significance level. (Negative values should be indicated by a minus sign. Round your answers to 3 decimal places.) H0: β1 = 0 H0: β2 = 0 H1: β1 ≠ 0 H1: β2 ≠ 0 H0 is rejected if t < 2.052 or t > 2.052arrow_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_forward
- 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…arrow_forwardA 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…arrow_forwardA 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…arrow_forward
- The 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_forwardSuppose 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_forwardThe options for part b are: head circumference or heightarrow_forward
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