please do b We have data from the National Confectioners Association on 6-years worth of candy sales whereour response is the amount of candy sold (in millions of dollars) and the predictor is the year ofsale.Amount of Candy Sold 1.993 2.041 2.0882.146 2.202 2.209Year200320042005200620072008(a)Estimate the fitted regression line using the above dataset.(b)Build a 95% confidence interval for the mean response when the predictor increasesby one unit.(c)based for a hypothesis test based on this table be supported by the confidence interval in (b).Justify briefly.Build the Analysis of Variance table for this linear model. Would a conclusion(d)for a hypothesis test on the slope of the regression line.Show that, in general, the F statistic is equivalent to the square of the T statistic(e)using the test statisticShow that, in general, it is equivalent to test whether the population slope is 0r/n – 2T ='п -V1- r2where r is the sample correlation between X and Y.

Simple linear regression model: A simple linear regression model is given as y^ = b0 + bx + e…

We have data from the National Confectioners Association on 6-years worth of candy sales where our response is the amount of candy sold (in millions of dollars) and the predictor is the year of sale. 11 O 04 1 O. 000

We have data from the National Confectioners Association on 6-years worth of candy sales where our response is the amount of candy sold (in millions of dollars) and the predictor is the year of sale. 11 O 04 1 O. 000

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

See similar textbooks

Similar questions

Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
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 average asking rent for 10 markets, and the corresponding monthly mortgage on the median priced home (including taxes and insurance) for 10 cities are given in Rent ($) Mortgage ($) City 1 840 539 City 2 1062 1002 City 3 823 626 City 4 779 711 City 5 796 655 City 6 1071 977 City 7 953 776 City 8 851 695 City 9 762 651 City 10 723 654 What is the simple linear regression model to predict the monthly mortgage on the median priced home, using average asking rent? Fill in the coefficient for the LINEAR independent variable (keep 2 decimal points).
In order to determine a realistic price for a new product that a company wants to market the company’s research department selected 10 sites thought to have essentially identical sales potential and offered the product in each at a different price. The resulting sales are recorded in the accompanying table: Price ($) Sales ($1,000s) 15.00 15 15.50 14 16.00 16 16.50 9 17.00 12 17.50 10 18.00 8 18.50 9 19.00 6 19.50 5 c). Find the equation of the sample regression line using Minitab. d). Interpret the meaning of the coefficients of the equation of the sample regression line.
Sarah 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 3.4348
Sarah is the office manager for a group of financial advisors who provide financial services forindividual clients. She would like to investigate whether a relationship exists between the numberof 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 aa random sample of six employees.Employee Presentations New Clients1 7 22 9 33 9 44 10 35 11 56 12 3Sarah would like to use simple regression analysis to estimate the number of new clients permonth based on the number of presentations made by the employee per month. The test statisticfor testing the hypothesis that the population coefficient of determination is greater than zero is________. A) 1.03 B) 1.45 C) -1.16 D) 0.35
Years of Work Experience and number of Job Offers of 10 job-seekers were as follows: Work Exp. 4 2 5 3 7 12 2 5 4 9 No. of Offers 7 1 8 4 13 19 3 11 9 15 a. Fit the regression equation of No. of Job Offers on Years of Work Experience. b. What will be the predicted number of offers for an applicant with 6 years of experience? c. Verify the relationship between the number of job offers and years of work experience using at least two relevant methods
A researcher recorded the number of e-mails received in a month and the number of online purchases made during that month for 50 people with an online presence. The resulting data were used to conduct a hypothesis test to investigate whether the slope of the population regression line relating number of e-mails received to number of online purchases is positive. What are the correct hypotheses for the test? H0:β1=0Ha:β1≠0H0:β1=0Ha:β1≠0 A H0:β1=0Ha:β1>0H0:β1=0Ha:β1>0 B H0:β1=0Ha:β1<0H0:β1=0Ha:β1<0 C H0:β1>0Ha:β1=0H0:β1>0Ha:β1=0 D H0:b1=0Ha:b1≠0 E
A sales manager collected the following data on annual sales for new customer accounts and the number of years of experience for a sample of 10 salespersons. Salesperson Years of Experience Annual Sales ($1000s) 1 1 80 2 3 97 3 4 92 4 4 102 5 6 103 6 8 111 7 10 119 8 10 123 9 11 117 10 13 136 Develop a scatter diagram for these data with years of experience as the independent variable. Develop an estimated regression equation that can be used to predict annual sales given the years of experience. Use the estimated regression equation to predict annual sales for a salesperson with 9 years of experience.
A random sample of 9 statistics students produced the following data, Midterm Exam Score, x Final Exam Score, y 81 49 62 23 76 84 26 58 96 33 38 36 10 15 15 83 81 28 where x measures the midterm exam score and y measures the final exam score. What is the estimate of the y = a x + b regression intercept coefficient?
Is there any multicollinearity problem in the above multiple regression model? How do you know? Risk of Stroke (%) Age Pressure Smoker (Yes=1) 12 57 152 0 24 67 163 0 13 58 155 0 56 86 177 1 28 59 196 0 51 76 189 0 18 56 155 1 31 78 120 0 37 80 135 1 15 78 98 0 22 71 152 0 36 70 173 1 15 67 135 1 48 77 209 0 15 60 199 0 36 82 119 1 8 66 166 0 34 80 125 1 3 62 117 0 37 59 207 1
A random sample of 9 statistics students produced the following data, Midterm Exam Score, x Final Exam Score, y 18 87 84 75 48 10 22 60 46 60 92 46 69 33 93 45 28 60 where x measures the midterm exam score and y measures the final exam score. What is the estimate of the y = a x + b regression slope coefficient?