I keep getting the answers incorrect. 12:10AAwww-awn.aleks.comO REGRESSION AND CORRELATIONPredictions from the least-.Can movie rental revenue be predicted?A movie studio wishes to determine the relationship between the revenuefrom rental of comedies on DVD and videotape and the revenue generatedfrom the theatrical release of such movies. The studio has the followingbivariate data from a sample of fifteen comedies released over the past fiveyears. These data give the revenue x from theatrical release (in millions ofdollars) and the revenue y from DVD and videotape rentals (in millions ofdollars) for each of the fifteen movies. Also shown are the scatter plot andthe least-squares regression line for the data. The equation for this line isy- 3,22 +0.15 x.Theater revenue,Rental revenue, y(in millions ofdollars)(in millions ofdollars)13.49.765.710.41661.510.227.42.81460.215.7127.62.21036.012.215.32.120.66.026.18.324.97.327.612.544.57.4Figure 148.915.531.55.2Send data to ExcelBased on the studio's data and the regression line, answer the following:1. Fill in the blank: For these data, values for rental revenue that areless than the mean of the values for rental revenue tend to be pairedwith values for theater revenue that are the mean of the valuesfor theater revenue.Choose one2. Fill in the blank: According to the regression equation, for anincrease of one million dollars in theater revenue, there is acorresponding of 0.15 million dollars in rental revenue.Choose one3. What was the observed rental revenue (in millions of dollars) when Inthe theater revenue was 61.5 million dollars?4. From the regression equation, what is the predicted rental revenue(in millions of dollars) when the theater revenue is 61.5 milliondollars? (Round your answer to at least one decimal place.)?ExplanationCheck 1. Fill in the blank: For these data, values for rental revenue that areless than the mean of the values for rental revenue tend to be pairedChoose onewith values for theater revenue that arethe mean of the valuesfor theater revenue.2. Fill in the blank: According to the regression equation, for anChoose oneincrease of one million dollars in theater revenue, there is acorrespondingof 0.15 million dollars in rental revenue.3. What was the observed rental revenue (in millions of dollars) whenthe theater revenue was 61.5 million dollars?4. From the regression equation, what is the predicted rental revenue(in millions of dollars) when the theater revenue is 61.5 milliondollars? (Round your answer to at least one decimal place.)

1. Fill in the blank: For these data, values for rental revenue that are less than the mean of the values for rental revenue tend to be paired with values for theater revenue that are. the mean of the values for theater revenue. 2. Fill in the blank: According to the regression equation, for an increase of one million dollars in theater revenue, there is a corresponding of 0.15 million dollars in rental revenue. 3. What was the observed rental revenue (in millions of dollars) when the theater revenue was 61.5 million dollars? 4. From the regression equation, what is the predicted rental revenue (in millions of dollars) when the theater revenue is 61.5 million dollars? (Round your answer to at least one decimal place.)

1. Fill in the blank: For these data, values for rental revenue that are less than the mean of the values for rental revenue tend to be paired with values for theater revenue that are. the mean of the values for theater revenue. 2. Fill in the blank: According to the regression equation, for an increase of one million dollars in theater revenue, there is a corresponding of 0.15 million dollars in rental revenue. 3. What was the observed rental revenue (in millions of dollars) when the theater revenue was 61.5 million dollars? 4. From the regression equation, what is the predicted rental revenue (in millions of dollars) when the theater revenue is 61.5 million dollars? (Round your answer to at least one decimal place.)

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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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?
Given the estimated least square regression line y=2.48+1.63x, and the coefficient of determination of 0.81, What is the value of correlation coefficient?
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 manufacturer of car batteries claims that the mean lifetime of their battery is 67 months. Thinking that this claim is inflated, graduate students buy a random sample of 72 car batteries from this manufacturer. How should they proceed? a) Perform a hypothesis test of H0:μ=67 versus Ha:μ>67 b) Perform a hypothesis test of H0:μ=67 versus Ha:μ<67 c) Use Simple linear regression
A researcher would like to predict the dependent variable Y from the two independent variables X1 and X2 for a sample of N=15 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test the significance of the overall regression model. Use a significance level α=0.02. X1 X2 Y 55.1 69.4 72.2 31.4 54.3 36.2 57.9 50 103.4 41.3 53.7 43.9 50.7 36.6 98.5 50.1 53.3 65.3 39.8 60.5 55.2 59.6 80.8 43.6 24.2 8.2 77 32.4 69.8 31 34.4 35.3 82.6 70.3 79.6 66.2 31.5 36.1 43.6 42.3 48.7 73.3 25.9 70.2 21.6 SSreg=SSres= R2= F=P-value = What is your decision for the hypothesis test? Reject the null hypothesis, H0:β1=β2=0 Fail to reject H0 What is your final conclusion? The evidence supports the claim that one or more of the regression coefficients is non-zero The evidence supports the claim that all of the regression coefficients are zero There is insufficient evidence to support the claim that at least one of the…