7q Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year inwhich there are 525 metric tons of lemon imports. Is the prediction worthwhile?Lemon ImportsCrash Fatality Rate 15.9 15.6230 26935748053815.415.414.9Find the equation of the regression line.+(Round the y-intercept to three decimal places as needed. Round the slope to four decimal places as needed.)

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Answered: Find the regression equation, letting…

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?
Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 500 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports 228 260 364 497 514 Crash Fatality Rate 16 15.8 15.6 15.4 14.9
Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 450 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports 228 261 350 489 511 Crash Fatality Rate 16.1 15.8 15.5 15.5 15.1 Find the equation of the regression line. y^=___+(__)x
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 electric power consumed each month by a chemical plant is thought to be related to the average ambient temperature ( x1 ), the number of days in the month ( x2 ), the average product purity ( x3 ), and the tons of product produced ( x4 ). The past year’s historical data are available and are presented in the following table:regression model is y = -102.7132 + 0.6054X1 + 8.9236X2 + 1.4374 X3 + 0.0136X4 a) Estimate sigma^2b.) Using ANOVA, test for significance of regression using α=0.05. Determine the critical value of the test statistic (2 decimal places only). c.) Using ANOVA, test for significance of regression using α=0.05. Determine the computed value of the test statistic d) Calculate R^2 for the computed regression model. Express your answer as a number less than 1 (NOT in %). e) Calculate R_adj^2 for the computed regression model. Express your answer as a number less than 1 (NOT in %).f) Test the significance of x3 at α=0.05. Determine the value of the test statistic. g)…
Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed actress/actor ages in various years, find the best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 32 years. Is the result within 5 years of the actual Best Actor winner, whose age was 53 years? Best Actress Best Actor27 4130 3529 3962 4432 5335 4943 5728 4861 4023 5746 4654 31 Find the equation of the regression line. y = (Round the constant to one decimal place as needed. Round the coefficient to three decimal places as needed.) The best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 32 years is years old. (Round to the nearest whole number as needed.) Is the result within 5 years of the actual Best Actor winner, whose age was 53 years? the predicted age is the actual winner's age.
Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed actress/actor ages in various years, find the best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 58 years. Is the result within 5 years of the actual Best Actor winner, whose age was 44 years? Best Actress Best Actor27 4129 3529 3658 4430 5131 4745 6228 4961 4022 5843 4557 35 Find the equation of the regression line. Round the constant to one decimal place as needed. Round the coefficient to three decimal places as needed.) The best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 58 years is Round to the nearest whole number as needed.) Is the result within 5 years of the actual Best Actor winner, whose age was 44 years? years old V the predicted age is V the actual winner's age.
Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed actress/actor ages in various years, find the best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 29 years. Is the result within 5 years of the actual Best Actor winner, whose age was 37 years? Best Actress Best Actor28 4229 3629 3760 4431 5131 4747 6228 5062 3921 5444 4252 35 Find the equation of the regression line. y=enter your response here+(enter your response here)x (Round the y-intercept to one decimal place as needed. Round the slope to three decimal places as needed.) Part 2 The best predicted age of the Best Actor winner given that the age of the Best Actress winner that year is 29 years is enter your response here years old. (Round to the nearest whole number as needed.) Part 3 Is the result within 5 years of the actual Best Actor winner, whose age was 37 years?…

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