Consider the following computer output from a multiple regression analysis relating the price of a used car to the variables: age of car, mileage, and safety rating.InterceptAge (Year)Mileage(in Thousands)Safety RatingAnswerCoefficients43835.55-22054.93- 1367.121579.51Does the sign of the coefficient for the variable safety rating make sense?CoefficientsStandard Error5654.622346.59111.37176.75t Stat7.752-9.399.- 12.2768.937P-value0.00000.00000.00000.0000O No, because it is expected that as safety rating increases then the price should also increase.O No, because it is expected that as safety rating increases then the price should decrease.O Yes, because it is expected that as safety rating increases then the price should also increase.O Yes, because it is expected that as safety rating increases then the price should decrease.TablesKeKeyboard She

Given,a multiple regression analysis relating the price of a car and variables - age of car,…

Answered: Does the sign of the coefficient for…

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...

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Find the equation of the regression line for the following data set. x 1 2 3 y 0 3 4
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?
A newspaper used an estimated regression equation to describe the relationship between y = error percentage for subjects reading a four-digit liquid crystal display and the independent variables x1 = level of backlight, x2 = character subtense, x3 = viewing angle, and x4 = level of ambient light. From a table given in the article, SSRegr = 21.6, SSResid = 22, and n = 30. What is the value of the test statistic F What is the P-value What is r2 What is Se
A car dealership would like to develop a regression model that would predict the number of cars sold per month by a dealership employee based on theemployee's number of years of sales experience. The accompanying regression output was developed based on a random sample of employees. ANOVA df SS Regression 1 79.909407 Residual 23 261.210593 Total 24 341.12 Coefficients Standard Error Intercept 7.271539 1.229763 Slope 0.539854 1. Predict the sales next month for an employee with 2.5 years of experience. The predicted sales is 8.6 cars. 2. Compute the coefficient of determination and interpret its meaning. The coefficient of determination is 0.234. 3. Do the sample data provide evidence that the model is useful for predicting average monthly sales for employees based on their sales experience using α=0.05? The test statistic is (Type an integer or decimal rounded to two decimal places as…
A car dealership would like to develop a regression model that would predict the number of cars sold per month by a dealership employee based on the employee's number of years of sales experience. The accompanying regression output was developed based on a random sample of employees. ANOVA df SS Regression 1 79.909407 Residual 23 261.210593 Total 24 341.12 Coefficients Standard Error Intercept 7.271539 1.229763 Slope 0.539854 Predict the sales next month for an employee with 2.5 years of experience. The predicted sales is _________ cars. (Type an integer or decimal rounded to one decimal place as needed.)
The following table shows the starting salary and profile of a sample of 10 employees in a certain call center agency. Run a multiple regression analysis with starting salary as the dependent variable (pesos) and GPA, years of experience and civil service ratings as the independent variables. Use .05 level of significance. Copy-paste the data and run the analysis using MS Excel. starting salary GPA Years of experience Civil Service Ratings 15000 80.1 1 79.5 15000 81.2 1 78.0 15500 81.3 2 79.0 16000 82.4 3 80.0 16200 83.4 3 85.0 17500 87.9 4 89.9 18000 90.3 5 89.1 16300 84.2 3 84.1 17000 87.0 4 89.0 17900 88.1 5 89.2 What is the computed R square of the resulting multiple linear regression and its interpretation?
A car dealership would like to develop a regression model that would predict the number of cars sold per month by a dealership employee based on theemployee's number of years of sales experience. The accompanying regression output was developed based on a random sample of employees. ANOVA df SS Regression 1 79.909407 Residual 23 261.210593 Total 24 341.12 Coefficients Standard Error Intercept 7.271539 1.229763 Slope 0.539854 0.203521 The coefficient of determination is 0.234 Test statistic= 0.704 P-value= 0.014 Construct a 95% confidence interval around the sample slope and interpret its meaning. The confidence interval is (__________,_________). (Type an integer or decimal rounded to three decimal places as needed.)
The systolic blood pressure dataset (in the third sheet of the spreadsheet linked above) contains the systolic blood pressure and age of 30 randomly selected patients in a medical facility. What is the equation for the least square regression line where the independent or predictor variable is age and the dependent or response variable is systolic blood pressure? Y=__________ X + ______________ Patient 7 is 67 years old and has a systolic blood pressure of 170 mm Hg. What is the residual? __________ mm Hg Is the actual value above, below, or on the line? What is the interpretation of the residual? (difference in actual &predicated bp, difference in age, the amount of systolic changes)

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