The regional transit authority for a major metropolitan area wants to determine whetherthere is any relationship between the age of a bus and the annual maintenance cost. Asample of 10 buses resulted in the following data. Age of Bus (year) Maintenance Cost ($) 1 350 2 370 2 480 2 520 2 590 3 550 4 750 4 800 5 790 5 950 a. Develop the least squares estimated regression equation.b. Test to see whether the two variables are significantly related with α = .5.c. Did the least squares line provide a good fit to the observed data? Explain.d. Develop a 95% prediction interval for the maintenance cost for a specific bus thatis 4 years old.

The regional transit authority for a major metropolitan area wants to determine whetherthere is any relationship between the age of a bus and the annual maintenance cost. Asample of 10 buses resulted in the following data. Age of Bus (year) Maintenance Cost ($) 1 350 2 370 2 480 2 520 2 590 3 550 4 750 4 800 5 790 5 950 a. Develop the least squares estimated regression equation.b. Test to see whether the two variables are significantly related with α = .5.c. Did the least squares line provide a good fit to the observed data? Explain.d. Develop a 95% prediction interval for the maintenance cost for a specific bus thatis 4 years old.

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?
A seafood-sales manager collected data on the maximum daily temperature, T, and the daily revenue from salmon sales, R, using sales receipts for 30 days selected at random. Using the data, the manager conducted a regression analysis and found the least-squares regression line to be Rˆ=126+2.37T. A hypothesis test was conducted to investigate whether there is a linear relationship between maximum daily temperature and the daily revenue from salmon sales. The standard error for the slope of the regression line is SEb1=0.65. Assuming the conditions for inference have been met, which of the following is closest to the value of the test statistic for the hypothesis test? t=0.274 A t=0.65 B t=1.54 C t=3.65 D t=193.85 E
A researcher collected data on the cholesterol level, CC, and the age, AA, of 24 people selected at random. Using the data, the researcher calculated the least-squares regression line to be Cˆ=182+2.2AC^=182+2.2A and the standard error of the slope to be 0.38. If the conditions for inference are met, which of the following is closest to the value of the test statistic to test the hypotheses H0:β=0H0:β=0 versus Ha:β≠0Ha:β≠0 ?
Suppose Wesley is a marine biologist who is interested in the relationship between the age and the size of male Dungeness crabs. Wesley collects data on 1,000 crabs and uses the data to develop the following least-squares regression line where ? is the age of the crab in months and ?ˆ is the predicted value of ?, the size of the male crab in cm. ?ˆ=8.1312+0.5226? What is the value of ?ˆ when a male crab is 23.0736 months old? Provide your answer with precision to two decimal places. ?ˆ = Interpret the value of ?. The value of ?ˆis the predicted size of a crab when it is 23.0736 months old. the predicted incremental increase in size for every increase in age by 23.0736 months. the predicted number of crabs out of the 1,000 crabs collected that will be 23.0736 months old. the probability that a crab will be 23.0736 months old.