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Intercept *₂ A study of 30 secretaries' yearly salaries (in thousands of dollars) was done. The researchers want to predict salaries from several other variables. The variables considered to be potential predictors 1 of salary are months of service (x₁). years of education (x₂), score on a standardized test (X₁), words per minute (wpm) typing speed (x4), and ability to take dictation in words per minutex, (xs). A multiple regression model with all five variables was run. X4 x₂ Assume that the residual plots show no violations of the conditions for using a linear regression model. a) What is the regression equation? y-9.191+ 0.114 x,+ 0.072x₂ + 0.097 x 0.013x + 0.064 x (Use integers or decimals for any numbers in the expression. Do not round.) The predicted salary is thousand dollars. (Round to one decimal place as needed.) 9.191 0.114 0.072 0.097 0.013 0.064 0.379 0.013 0.022 0.037 0,309 0.028 24 251 8.769 3.273 2.622 0.042 2.286 b) From this model, what is the predicted salary y (in thousands of dollars) of a secretary with 14 years (168 months) of experience, 10th grade education (10 years of education), a 55 on the standardized test, 62 wpm typing speed, and the ability to take 31 wpm dictation?

Intercept *₂ A study of 30 secretaries' yearly salaries (in thousands of dollars) was done. The researchers want to predict salaries from several other variables. The variables considered to be potential predictors 1 of salary are months of service (x₁). years of education (x₂), score on a standardized test (X₁), words per minute (wpm) typing speed (x4), and ability to take dictation in words per minutex, (xs). A multiple regression model with all five variables was run. X4 x₂ Assume that the residual plots show no violations of the conditions for using a linear regression model. a) What is the regression equation? y-9.191+ 0.114 x,+ 0.072x₂ + 0.097 x 0.013x + 0.064 x (Use integers or decimals for any numbers in the expression. Do not round.) The predicted salary is thousand dollars. (Round to one decimal place as needed.) 9.191 0.114 0.072 0.097 0.013 0.064 0.379 0.013 0.022 0.037 0,309 0.028 24 251 8.769 3.273 2.622 0.042 2.286 b) From this model, what is the predicted salary y (in thousands of dollars) of a secretary with 14 years (168 months) of experience, 10th grade education (10 years of education), a 55 on the standardized test, 62 wpm typing speed, and the ability to take 31 wpm dictation?

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.5: Correlation And Causation
Problem 2AGP
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*2 A study of 30 secretaries' yearly salaries (in thousands of dollars) was done. The researchers want to predict salaries from several other variables. The variables considered to be potential predictors 1 of salary are months of service (x₁). years of education (x₂), score on a standardized test (x3), words per minute (wpm) typing speed (x4), and ability to take dictation in words per minutex, (xs). A multiple regression model with all five variables was run Variable Intercept y-9.191+ 0.114 x,+ 0.072x₂ 0.097 x 0.013 x₁ +0.064 x (Use integers or decimals for any numbers in the expression. Do not round.) Assume that the residual plots show no violations of the conditions for using a linear regression model. a) What is the regression equation? X4 X5 The predicted salary is thousand dollars. (Round to one decimal place as needed.) Coef 9.191 0.114 0.072 0.097 0.013 0.064 Std. Error 0.379 0,013 0.022 0.037 0,309 0,028 t-value 24,251 8.769 3.273 2.622 0.042 2.286 b) From this model, what is the predicted salary y (in thousands of dollars) of a secretary with 14 years (168 months) of experience, 10th grade education (10 years of education), a 55 on the standardized test, 62 wpm typing speed, and the ability to take 31 wpm dictation?
Transcribed Image Text:*2 A study of 30 secretaries' yearly salaries (in thousands of dollars) was done. The researchers want to predict salaries from several other variables. The variables considered to be potential predictors 1 of salary are months of service (x₁). years of education (x₂), score on a standardized test (x3), words per minute (wpm) typing speed (x4), and ability to take dictation in words per minutex, (xs). A multiple regression model with all five variables was run Variable Intercept y-9.191+ 0.114 x,+ 0.072x₂ 0.097 x 0.013 x₁ +0.064 x (Use integers or decimals for any numbers in the expression. Do not round.) Assume that the residual plots show no violations of the conditions for using a linear regression model. a) What is the regression equation? X4 X5 The predicted salary is thousand dollars. (Round to one decimal place as needed.) Coef 9.191 0.114 0.072 0.097 0.013 0.064 Std. Error 0.379 0,013 0.022 0.037 0,309 0,028 t-value 24,251 8.769 3.273 2.622 0.042 2.286 b) From this model, what is the predicted salary y (in thousands of dollars) of a secretary with 14 years (168 months) of experience, 10th grade education (10 years of education), a 55 on the standardized test, 62 wpm typing speed, and the ability to take 31 wpm dictation?
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