The general manager of an engineering firm wants to know whether a technical artist's experience influences the quality of his or her work. A random sample of 24 artists is selected and their years of work experience and quality rating (as assessed by their supervisors) recorded. Work experience (EXPER) is measured in years and quality rating (RATING) takes a value of 1 through 7, with 7 = excellent and 1 = poor. The simple regression model RATING = ẞ1 + ẞ₂EXPER+ € is proposed. The least squares estimates of the model, and the standard errors of the estimates, are RATING= 3.204 +0.076EXPER (se) (0.709) (0.044) (a) Interpret the coefficient of EXPER. (b) Construct a 95% confidence interval for B2, the slope of the relationship between quality rating and experience. In what are you 95% confident? (c) Test the null hypothesis that ẞ2 is zero against the alternative that it is not using a two-tail test and the α = 0.05 level of significance. What do you conclude? (d) Test the null hypothesis that ẞ2 is zero against the one-tail alternative that it is positive at the a = €0.05 level of significance. What do you conclude? (e) For the test in part (c), the p-value is 0.0982. If we choose the probability of a Type-I error to be a = 0.05, do we reject the null hypothesis, or not, just based on an inspection of the p-value?

Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter1: Functions
Section1.2: The Least Square Line
Problem 8E
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The general manager of an engineering firm wants to know whether a technical artist's experience influences the quality of his or her work. A random sample of 24 artists
is selected and their years of work experience and quality rating (as assessed by their supervisors) recorded. Work experience (EXPER) is measured in years and quality
rating (RATING) takes a value of 1 through 7, with 7 = excellent and 1 = poor. The simple regression model RATING = ẞ1 + ẞ₂EXPER+ € is proposed. The least
squares estimates of the model, and the standard errors of the estimates, are
RATING= 3.204 +0.076EXPER
(se)
(0.709) (0.044)
(a) Interpret the coefficient of EXPER.
(b) Construct a 95% confidence interval for B2, the slope of the relationship between quality rating and experience. In what are you 95% confident?
(c) Test the null hypothesis that ẞ2 is zero against the alternative that it is not using a two-tail test and the α = 0.05 level of significance. What do you
conclude?
(d) Test the null hypothesis that ẞ2 is zero against the one-tail alternative that it is positive at the a = €0.05 level of significance. What do you conclude?
(e) For the test in part (c), the p-value is 0.0982. If we choose the probability of a Type-I error to be a = 0.05, do we reject the null hypothesis, or not, just
based on an inspection of the p-value?
Transcribed Image Text:The general manager of an engineering firm wants to know whether a technical artist's experience influences the quality of his or her work. A random sample of 24 artists is selected and their years of work experience and quality rating (as assessed by their supervisors) recorded. Work experience (EXPER) is measured in years and quality rating (RATING) takes a value of 1 through 7, with 7 = excellent and 1 = poor. The simple regression model RATING = ẞ1 + ẞ₂EXPER+ € is proposed. The least squares estimates of the model, and the standard errors of the estimates, are RATING= 3.204 +0.076EXPER (se) (0.709) (0.044) (a) Interpret the coefficient of EXPER. (b) Construct a 95% confidence interval for B2, the slope of the relationship between quality rating and experience. In what are you 95% confident? (c) Test the null hypothesis that ẞ2 is zero against the alternative that it is not using a two-tail test and the α = 0.05 level of significance. What do you conclude? (d) Test the null hypothesis that ẞ2 is zero against the one-tail alternative that it is positive at the a = €0.05 level of significance. What do you conclude? (e) For the test in part (c), the p-value is 0.0982. If we choose the probability of a Type-I error to be a = 0.05, do we reject the null hypothesis, or not, just based on an inspection of the p-value?
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