Which of the following conditions appear to be met based on the residual plot? I. The true relationship between xx and yy is not linear. II. Observations are independent. III. The standard deviation of yy does not vary with xx. I only A

Which of the following conditions appear to be met based on the residual plot? I. The true relationship between xx and yy is not linear. II. Observations are independent. III. The standard deviation of yy does not vary with xx. I only A

Name: Russell plans on constructing a confidence interval for the slope of a
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Description: Russell plans on constructing a confidence interval for the slope of a regression line. He creates the residual plot shown to check the conditions for creating the interval. Which of the following conditions appear to be met based on the residual plo

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 major credit card company is interested in whether there is a linear relationship between its internal rating of a customer’s credit risk and that of an independent rating agency. The company collected a random sample of 200 customers and used the data to test the claim that there is a linear relationship. The following hypotheses were used to test the claim. H0:β1=0Ha:β1≠0 The test yielded a t-value of 3.34 with a corresponding p-value of 0.001. Which of the following is the correct interpretation of the p-value? If the alternative hypothesis is true, the probability of observing a test statistic at least as extreme as 3.34 is 0.001. If the alternative hypothesis is true, the probability of observing a test statistic at least as extreme as 3.34 is 0.001. A If the alternative hypothesis is true, the probability of observing a test statistic of 3.34 or greater is 0.001. If the alternative hypothesis is true, the probability of observing a test statistic of 3.34 or greater…
Use the following linear regression equation to answer the questions. x1 = 1.7 + 3.9x2 – 8.5x3 + 2.2x4 Suppose x2 increased by 2 units. What would be the expected change in x1? Suppose x2 increased by 4 units. What would be the expected change in x1? (e) Suppose that n = 18 data points were used to construct the given regression equation and that the standard error for the coefficient of x2 is 0.454. Construct a 99% confidence interval for the coefficient of x2. (Use 2 decimal places.) lower limit ? upper limit ? (f) Using the information of part (e) and level of significance 10%, test the claim that the coefficient of x2 is different from zero. (Use 2 decimal places.) t ? t critical ± ?
The results of a sample of 7 data points are presented below in terms of the Average Daily Temperature (oF) and the Average Monthly Precipitation (inches): Average Daily temperature x 86 81 83 89 80 74 64 Average Monthly Precipitation y 3.4 1.8 3.5 3.6 3.7 1.5 0.2 d- Determine the regression line equation e- Plot the regression line on the scatter plot (on same graph) f- Calculate the standard error of estimate g- Find the 95% prediction interval for the 95oF average daily temperature
The following data are the monthly salaries and the grade point averages for students who obtained a bachelor's degree in business administration. GPA Monthly Salary ($) 2.6 3,600 3.4 3,900 3.6 4,300 3.2 3,800 3.5 4,200 2.9 3,900 The estimated regression equation for these data is and . Use Table 1 of Appendix B. a. Develop a point estimate of the starting salary for a student with a GPA of (to 1 decimal). b. Develop a confidence interval for the mean starting salary for all students with a GPA (to 2 decimals). ( , ) c. Develop a prediction interval for Ryan Dailey, a student with a GPA of (to 2 decimals). ( , ) d. Discuss the differences in your answers to parts (b) and (c).
A scientist is interested in whether there is a linear relationship between the amount of mercury in a lake and the surface area of the lake. The scientist collected data on 22 lakes of a similar type selected at random and used the data to test the claim that there is a linear relationship. The following hypotheses were used to test the claim. H0:β=0 Ha:β≠0 The test yielded a t-value of 2.086 with a corresponding p-value of 0.05. Which of the following is the correct interpretation of the p-value? A. If there is a linear relationship between the amount of mercury in a lake and the surface area of the lake, the probability of observing a test statistic as extreme as 2.086 or more extreme is 0.05 B. If there is a linear relationship between the amount of mercury in a lake and the surface area of the lake, the probability of observing a test statistic of 2.086 is 0.05. C. If there is not a linear relationship between the amount of mercury in a lake and the surface area of the lake, the…