Introduction To Statistics And Data Analysis
6th Edition
ISBN: 9781337793612
Author: PECK, Roxy.
Publisher: Cengage Learning,
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Chapter 13.2, Problem 17E
a.
To determine
Find the estimated standard deviation of the statistic b.
b.
To determine
Find the 95% confidence interval for
c.
To determine
Explain whether the interval in Part (b) suggest that
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In exercise 12, the following data on x = average daily hotel room rate and y = amount spent on entertainment (The Wall Street Journal, August 18, 2011) lead to the estimated regression equation ŷ = 17.49 + 1.0334x. For these data SSE = 1541.4. Use Table 1 of Appendix B.Click on the datafile logo to reference the data.
a. Predict the amount spent on entertainment for a particular city that has a daily room rate of $89 (to 2 decimals).$
b. Develop a 95% confidence interval for the mean amount spent on entertainment for all cities that have a daily room rate of $89 (to 2 decimals).$ to $
c. The average room rate in Chicago is $128. Develop a 95% prediction interval for the amount spent on entertainment in Chicago (to 2 decimals).$ to $
In exercise 12, the following data on x = average daily hotel room rate and y = amount spent on entertainment (The Wall Street Journal, August 18, 2011) lead to the estimated regression equation ŷ = 17.49 + 1.0334x. For these data SSE = 1541.4.Click on the datafile logo to reference the data. Use Table 1 of Appendix B.
a. Predict the amount spent on entertainment for a particular city that has a daily room rate of $89 (to 2 decimals).$
b. Develop a 95% confidence interval for the mean amount spent on entertainment for all cities that have a daily room rate of $89 (to 2 decimals).$ to $
c. The average room rate in Chicago is $128. Develop a 95% prediction interval for the amount spent on entertainment in Chicago (to 2 decimals).
Use the following information from a multiple regression analysis.
n=15
b1=2
b2=6
Sb1=1.4
Sb2=0.5
a.
Which variable has the largest slope, in units of a t statistic?
b.
Construct a
90%
confidence interval estimate of the population slope,
β1.
c.
At the
0.10
level of significance, determine whether each independent variable makes a significant contribution to the regression model. On the basis of these results, indicate the independent variables to include in this model.
Chapter 13 Solutions
Introduction To Statistics And Data Analysis
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- A researcher developed a regression model to predict the cost of a meal based on the summated rating (sum of ratings for food, decor,and service) and the cost per meal for 12 restaurants. The results of the study show that b1=1.4379 and Sb1=0.1397. a. At the 0.05 level of significance, is there evidence of a linear relationship between the summated rating of a restaurant and the cost of a meal? b. Construct a 95% confidence interval estimate of the population slope, β1. a. Determine the hypotheses for the test. Choose the correct answer below. A. H0: β1=0 H1: β1≠0 B. H0: β0≤0 H1: β0>0 C. H0: β1≤0 H1: β1>0 D. H0: β0≥0 H1: β0<0 E. H0: β1≥0 H1: β1<0 F. H0: β0=0 H1: β0≠0 Compute the test statistic. The test statistic is ? (Round to two decimal places as needed.) Determine the critical value(s). The critical value(s) is(are) ? (Use a comma to separate answers as needed.…arrow_forwardIn Exercises, presume that the assumptions for regression inferences are met.Plant Emissions. Following are the data on plant weight and quantity of volatile emissions from Exercise. x 57 85 57 65 52 67 62 80 77 53 68 y 8.0 22.0 10.5 22.5 12.0 11.5 7.5 13.0 16.5 21.0 12.0 a. Obtain a point estimate for the mean quantity of volatile emissions of all (Solanum tuberosum) plants that weigh 60 g.b. Find a 95% confidence interval for the mean quantity of volatile emissions of all plants that weigh 60 g.c. Find the predicted quantity of volatile emissions for a plant that weighs 60 g.d. Determine a 95% prediction interval for the quantity of volatile emissions for a plant that weighs 60 g.ExerciseApplying the Concepts and SkillsIn Exercises, we repeat the information from Exercises. For each exercise here, discuss what satisfying Assumptions 1–3 for regression inferences by the variables under consideration would mean.arrow_forwardThe following data represent the yield on 30 consecutive batches of ceramic substrate to which a metal coating has been applied by a vapor-deposition process. a. Create a Histogram. b. What is the sample mean of the data? c. What is the sample standard deviation of the data? d. What is the skewness of the data (Pearson's first mode of coefficient)? What could you conclude? e. What is the kurtosis of the data? What could you conclude? (show solution)arrow_forward
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