3 4141a. Develop the estimated regression equation that relates annual maintenance expense (in hundreds of dollars) to weekly usage hours (to 3decimals).ExpenseWeekly Usageb. Test the significance of the relationship in part (a) at a 0.05 level of significance.Compute the value of the F test statistic (to 2 decimals).The p value is- Select your answer -What is your conclusion?Select your answer -C. Jensen expects the new machine to be used 30 hours per week. What is the expected annual maintenance expense in hundreds of dollars (to2 decimals)?hundredDevelop a 95% prediction interval for the company's annual maintenance expense for this machine (to 2 decimals).(Shundred, shundred )d. If the maintenance contract costs $3000 per year, would you recommend purchasing the contract for the new machine in part (c)? Why or whynot?Select your answer- Jensen Tire & Auto is in the process of deciding whether to purchase a maintenance contract for its new computer wheel alignment and balancingmachine. Managers feel that maintenance expense should be related to usage, and they collected the following information on weekly usage(hours) and annual maintenance expense (in hundreds of dollars).Weekly UsageAnnual(hours)Maintenance Expense1618132323313138354820322734344043534141a. Develop the estimated regression eguation that relates annual maintenance expense (in hundreds of dollars) to weekly usage hours (to 3decimals).ExpenseWeekly Usageb. Test the significance of the relationship in part (a) at a 0.05 level of significance.Compute the value of the F test statistic to 2 decinals).

Since you have posted a question with multiple sub-parts, we will solve first three sub- parts for…

Answered: Tensen Tire & Auto IS in the process of…

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter4: Equations Of Linear Functions

Section4.6: Regression And Median-fit Lines

Problem 4GP

See similar textbooks

Similar questions

Mumbai Electronics is planning to extend its marketing region from the western United States to include the midwestern states. In order to predict its sales in this new region, the company has asked you to develop a linear regression of DVD system sales on price, using the following data supplied by the marketing department: Sales 418 384 343 407 432 386 444 427 Price 98 194 231 207 89 255 149 195 a. Use an unbiased estimation procedure to find an estimate of the variance of the error terms in the population regression. b. Use an unbiased estimation procedure to find an estimate of the variance of the least squares estimator of the slope of the population regression line. c. Find a 90% confidence interval for the slope of the population regression line.
Which of the following is not an example of systematic error in an observational study? A cross-sectional study recruits participants that are willing to sign up outside of a major university and meet the inclusion and exclusion criteria to take part in the survey relating unsafe sex habits to STIs. A researcher is interested in the relationship between coffee drinking and lung cancer, and after careful multivariate linear regression modeling determines that a significant percentage of the relationship is due to another variable, cigarette smoking. An observational study recruits participants for a study looking at Alzheimer’s disease due to exposure to industrial hazards by asking participants to recall their exposure over the past 10 years. data-entry specialist responsible for adding in fasting glucose levels to a database accidentally skipped an observation during the input phase of data cleaning.
Which of the following circumstances would likely produce a regression model with very “good fit”. Group of answer choices Using consumption expenditures as a LHS variable and disposable income as a RHS variable Using obesity rates in an area as a LHS variable and number of ice cream shops in the area as a RHS variable Using family size as a LHS variable and college tuition costs as a RHS variable Using number of cops in an area as a LHS variable and number of donut shops in an area as a RHS variable Using height as a LHS variable and income as a RHS variable
If there is no significant correlation between the response and explanatory variables, would the slope of the regression line be (a) positive (b) negative (c) zero?
Bill 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 2 1 2 8 2 3 9 4 4 10 3 5 11 5 6 12 6 Bill 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 average number of new clients per month for an employee who made 20 presentations per month is ________. 5.02 5.45 3.43 8.69
The marketing manager of a chain of stores needed information about theeffectiveness of television advertising on weekly sales. The manager collected data from 25 randomly selected stores. For each store, the variables “store sales” and “TV advertising” were recorded per week.Both variables are recorded in euros (i.e. 1 unit=€1).You are given the following SPSS output. please see Image attached. Answer the following questions:(1) Test if television advertising generally affects the sales of this store. Use a 5% level of significance.(2) Write down the estimated regression model and interpret the coefficients. (3) Write down the value of the coefficient of determination and explain it. Is the fitting ofyour regression model good?(4) What is the value of the correlation coefficient between weekly sales and weeklyexpenditures on television advertising? Interpret it.(5) Predict the weekly sales when television advertising is €700.
The regional transit authority for a major metropolitan area wants to determine whether there is any relationship between the age of a bus and the annual maintenance cost. A sample of 10 buses resulted in the data in Worksheet 2. Worksheet 2 Age of a Bus (years) Maintenance Cost ($) 1 350 2 370 2 480 2 520 2 590 3 550 4 750 4 800 5 790 5 950 Develop a scatter diagram with the age of a bus as the independent variable. Develop the estimated regression equation that can be used to predict the maintenance cost given the age of a bus. Determine the coefficient of determination, and interpret its meaning in this problem. At the 0.05 level of significance, is there evidence of a linear relationship between the age of a bus and the annual maintenance cost.
Give an example of a research question that would be suitable for computing a: a) Correlation coefficient b) Regression line
Suppose that a kitchen cabinet warehouse company would like to be able to predict the area of a customer’s kitchen using the number of cabinets and the kitchen ceiling height. To do so data is collected on the following variables from a random sample of customers: Area – area of the kitchen in square feet Height – ceiling height in the kitchen (from floor to ceiling) in inches Cabinets – number of cabinets in the kitchen Suppose that a multiple linear regression model was fit to the data and that the following output resulted: Coefficients: (Intercept)HeightCabinets Estimate-57.98771.2760.3393 Std. Error8.63820.26430.1302 t value -6.7134.8282.607 Pr(>|t|)2.75e-074.44e-050.0145 What is the predicted area of a kitchen with a height of 96 inches and 10 cabinets? Report your answer to 1 decimal place. square feet
Suppose that a kitchen cabinet warehouse company would like to be able to predict the area of a customer’s kitchen using the number of cabinets and the kitchen ceiling height. To do so data is collected on the following variables from a random sample of customers: Area – area of the kitchen in square feet Height – ceiling height in the kitchen (from floor to ceiling) in inches Cabinets – number of cabinets in the kitchen Suppose that a multiple linear regression model was fit to the data and that the following output resulted: Coefficients: (Intercept)HeightCabinets Estimate-57.98771.2760.3393 Std. Error8.63820.26430.1302 t value -6.7134.8282.607 Pr(>|t|)2.75e-074.44e-050.0145 10 Question 10 This is not a form; we suggest that you use the browse mode and read all parts of the question carefully. Which of the following is the correct interpretation of the coefficient for Cabinets? For a kitchen with a given ceiling height, the average number of cabinets…
Suppose that a kitchen cabinet warehouse company would like to be able to predict the area of a customer’s kitchen using the number of cabinets and the kitchen ceiling height. To do so data is collected on the following variables from a random sample of customers: Area – area of the kitchen in square feet Height – ceiling height in the kitchen (from floor to ceiling) in inches Cabinets – number of cabinets in the kitchen Suppose that a multiple linear regression model was fit to the data and that the following output resulted: Coefficients: (Intercept)HeightCabinets Estimate-57.98771.2760.3393 Std. Error8.63820.26430.1302 t value -6.7134.8282.607 Pr(>|t|)2.75e-074.44e-050.0145 Why is the interpretation of the constant term (i.e. "intercept") not meaningful for this example? The predicted area will be negative when the number of cabinets is zero and the height of the kitchen is also zero. But we cannot have a negative area, nor a kitchen ceiling height of 0 inches.…
. 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…

SEE MORE QUESTIONS

Recommended textbooks for you

Glencoe Algebra 1, Student Edition, 9780079039897…

Algebra

ISBN:

9780079039897

Author:

Carter

Publisher:

McGraw Hill

Big Ideas Math A Bridge To Success Algebra 1: Stu…

Algebra

ISBN:

9781680331141

Author:

HOUGHTON MIFFLIN HARCOURT

Publisher:

Houghton Mifflin Harcourt

Glencoe Algebra 1, Student Edition, 9780079039897…

Algebra

ISBN:

9780079039897

Author:

Carter

Publisher:

McGraw Hill

Big Ideas Math A Bridge To Success Algebra 1: Stu…

Algebra

ISBN:

9781680331141

Author:

HOUGHTON MIFFLIN HARCOURT

Publisher:

Houghton Mifflin Harcourt

SEE MORE TEXTBOOKS