1.8.9.actice ProblemsJensen Tire & Auto is in the process of deciding whether to purchase a maintenance contract for its new computer wheel alignment and balancing machine. Managers feel that maintenanceexpense should be related to usage, and they collected the following information on weekly usage (hours) and annual maintenance expense (in hundreds of dollars).AnnualWeekly Usage(hours)Maintenance ExpenseO1818152325313338O374822322934364045534341a. Develop the estimated regression equation that relates annual maintenance expense (in hundreds of dollars) to weekly usage hours (to 3 decimals).Expense =+Weekly 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 less than 0.01What is your conclusion?SConclude that there is a significant relationship between expense and weekly usagec. Jensen expects the new machine to be used 30 hours per week. What is the expected annual maintenance expense in hundreds of dollars (to 2 decimals)?hundredDevelop a 95% prediction interval for the company's annual maintenance expense for this machine (to 2 decimals).hundred )($)hundred, $QDDDII$10888FOF7FA&7I●▸1!222T380E$4R%5T6YU148(I9OOPFI+[.A2ME-

Given: The independent variable X is Weekly usage (hours) The dependent variable Y is Annual…

Answered: a. Develop the estimated regression…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Consider a regression model. The coefficient of determination (R2) gives the proportion of the variability in the dependent variable that is explained by the regression equation. True False
You are studying the relationship between age and lung function measured as forced expiratory volume in 1 min. In a regression analysis is lung function the best option for Y? O Yes O No
Does how long young children remain at the lunch table help predict how much they eat? Twenty toddlers were observed over several months at a nursery school. "Time" is the average number of minutes a child spent at the table when lunch was served. "Calories" is the average number of calories the child consumed during lunch, calculated from careful observation of what the child ate each day. A regression was run and the results were: = 114 + 2.4*x R² = 0.68 r = 0.822 Predict the number of calories a toddler consumes who remains at the table for 14.5 minutes (round your answer to two decimal places)
Based on the analyst's data and regression line, complete the following. For these data, values for earnings per share that are greater than the mean of the values for earnings per share tend to be paired with current stock prices that are (greater than, lesser than) the mean of the current stock prices. According to the regression equation, for an increase of one dollar in earnings per share, there is a corresponding increase of how many dollars in current stock price?
4:42 ul LTE AA www-awn.aleks.com O REGRESSION AND CORRELATION Predictions from the least-square. The well-known psychologist Dr. Elbod has established what he calls his Generalized Anxiety Scale (GAS). The GAS, which is a scale from o to 10, measures the "general anxiety" of an individual, with higher GAS scores corresponding to more anxiety. (Dr. Elbod's assessment of anxiety is based on a variety of measurements, both physiological and psychological.) We're interested in making predictions about individuals' sleep behavior based on their GAS scores. The bivariate data below give the GAS score (denoted by x) and the number of hours of sleep last night (denoted by y ) for each of the fifteen adults in a study. The least-squares regression line for these data has equation =8.36-0.25x. This line, along with a scatter plot of the sample data, is shown in Figure 1. Sleep time, y (in hours) GAS score, x 6.0 8.1 6.5 5.9 10- 5.1 6.0 7.9 5.7 7.1 6.7 1.0 7.4 8.1 7.2 3.0 6.9 2.1 8.1 9.0 5.8 9.2…
Below is some of the regression output from a regression of the amount various customers paid for a new car (expressed in dollars) versus the age of the customer (expressed in years), the number of previous cars the customer had purchased from the dealership in the past, a dummy variable indicating the gender of the customer (=1 for a Man and = 0 for a woman), and an interactive term the multiplies the age of the customer with the gender dummy variable. Regression Statistics Multiple R 0.963 R Square Adjusted R Square Standard Error Observations 20 ANOVA df SS MS F Significance F Regression 24686354.49 6171589 47.8 2.3289E-08 Residual 129243 Total 26625000…
The owner of Showtime Movie Theatres Inc. would like to predict weekly gross revenue as a function of advertising expenditures. Use 0.05 level of significance.Historical data for a sample of eight weeks follow: Weekly Gross Renvenue Telelvision Newspaper Adveritising ($1000s) Adveritising a) Develop an estimated regression equation to predict weekly gross revenue as a function of advertising expenditures. ($1000s) ($1000s) 96 5.0 1.5 90 20 2.0 b) Explain in simg when 1000s are spent on television and newspaper then the revenue will in 95 4.0 1.5 92 2.5 2.5 c) Predict weekly 95 3.0 3,3 94 3.5 2.3 d) What is the R2 value? 0.9190 94 2.5 4.2 94 3.0 2.5 e) What is the Hypothesis Test? Use the t test to determine the significance of each independent variable. State the t test, p-values, and your conclusion. g) What is the cor Reject Ho SUMMARY OUTPUT pression Statstica Mutiple R 0.958663444 0.9190356 R Square 0.88664984 Adusted R Square Standard Eror 0.642587303 Obervations ANOVA Syaicance…
I need help with this last part of this exercise.
I need help finding the answers for A,B,and C
Increase in sales (percent) An advertising firm wishes to demonstrate to its clients the effectiveness of the advertising campaigns it has conducted. The following bivariate data on twelve recent campaigns, including the cost of each campaign (in millions of dollars) and the resulting percentage increase in sales following the campaign, were presented by the firm. Based on these data, we would compute the least-squares regression line to be y = 6.16+0.18x, with x representing campaign cost and y representing the resulting percentage increase in sales. (This line is shown below, along with a scatter plot of the data.) Increase in sales, y Campaign cost, x (in millions of dollars) (percent) 3.02 6.91 7.2+ 1.92 6.80 3.83 6.85 6.8- 1.40 6.37 6.6 - 3.12 6.42 3.56 6.82 6.4- 4.06 6.94 6.2 1.64 6.56 6- 2.06 6.50 1.62 6.18 1.5 2.5 3.5 6.66 Campaign cost (in millions of dollars) 2.87 2.25 6.61 Send data to calculator Based on the firm's data and the regression line, complete the following. (a)…
The table shows a part of an output of a linear regression model predicting the average fare on different flight routes. Data Table Regression Table Coefficient Constant 95.80976147 COUPON −9.61654124 DISTANCE 0.080733811 PAX −0.000167343 What is the difference in prediction of the following two routes? Route A that is 3,000 miles, with COUPON=1.5 and PAX=6,000 Route B that is 3,000 miles, with COUPON=1.2 and PAX=6,000.
The accompanying data are the number of wins and the earned run averages (mean number of earned runs allowed per nine innings pitched) for eight baseball pitchers in a recent season. Find the equation of the regression line. Then construct a scatter plot of the data and draw the regression line. Then use the regression equation to predict the value of y for each of the given x-values, if meaningful. If the x-value is not meaningful to predict the value of y, explain why not. (a) x = 5 wins Click the icon to view the table of numbers of wins and earned run average. (b) x = 10 wins (c) x = 21 wins (d) x = 15 wins ERA 6- ERA 6- AERA 6- ERA 6- 4- 4- 4- 4- 2- 2- 2- 2- 0+ 6 0- 0- 0- 12 18 24 6. 12 18 24 12 18 24 6 12 18 24 Wins Wins Wins Wins (a) Predict the ERA for 5 wins, if it is meaningful. Select the correct choice below and, if necessary, fill in the answer box within your choice. A. ŷ= (Round to two decimal places as needed.) B. It is not meaningful to predict this value of y because…

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