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A paper describes a study to determine the effects of several keyboard characteristics on typing speed. One of the variables considered was the front-to-back surface angle of the keyboard. Minitab output resulting from fitting the simple linear regression model with x = surface angle (degrees) and y typing speed (words per minute) is given below. Regression Analysis: Typing Speed versus Surface Angle = The regression equation is Typing Speed Predictor Constant Surface Angle = 60.0 +0.0036 Surface Angle Coef 60.0286 SE Coef T P 0.00357 0.2466 0.03823 243.45 0.000 0.09 0.931 S = 0.511766 R-Sq = 0.3% R-Sq (adj) = 0.0% Analysis of Variance Source DF SS MS F P Regression 1 0.0023 0.0023 0.01 0.931 Residual 3 0.7857 0.2619 Error Total 4 0.788 (a) Assuming that the basic assumptions of the simple linear regression model are reasonably met, carry out a hypothesis test using α = 0.05 to decide if there is a useful linear relationship between x and y. Calculate the test statistic. (Enter your answer to two decimal places.) Calculate the test statistic. (Enter your answer to two decimal places.) t = What is the P-value for this test? (Enter your answer to three decimal places.) P-value = What can you conclude? Reject Ho. We do not have convincing evidence of a useful linear relationship between typing speed and surface angle. Do not reject Ho. We do not have convincing evidence of a useful linear relationship between typing speed and surface angle. Reject Ho. We have convincing evidence of a useful linear relationship between typing speed and surface angle. Do not reject Ho. We have convincing evidence of a useful linear relationship between typing speed and surface angle. (b) Are the values of s̟ and r² consistent with the conclusion from part (a)? Explain. e and Se show almost no linear relationship between the two variables. No, 2 Yes, r₂ and s show almost no linear relationship between the two variables.

A paper describes a study to determine the effects of several keyboard characteristics on typing speed. One of the variables considered was the front-to-back surface angle of the keyboard. Minitab output resulting from fitting the simple linear regression model with x = surface angle (degrees) and y typing speed (words per minute) is given below. Regression Analysis: Typing Speed versus Surface Angle = The regression equation is Typing Speed Predictor Constant Surface Angle = 60.0 +0.0036 Surface Angle Coef 60.0286 SE Coef T P 0.00357 0.2466 0.03823 243.45 0.000 0.09 0.931 S = 0.511766 R-Sq = 0.3% R-Sq (adj) = 0.0% Analysis of Variance Source DF SS MS F P Regression 1 0.0023 0.0023 0.01 0.931 Residual 3 0.7857 0.2619 Error Total 4 0.788 (a) Assuming that the basic assumptions of the simple linear regression model are reasonably met, carry out a hypothesis test using α = 0.05 to decide if there is a useful linear relationship between x and y. Calculate the test statistic. (Enter your answer to two decimal places.) Calculate the test statistic. (Enter your answer to two decimal places.) t = What is the P-value for this test? (Enter your answer to three decimal places.) P-value = What can you conclude? Reject Ho. We do not have convincing evidence of a useful linear relationship between typing speed and surface angle. Do not reject Ho. We do not have convincing evidence of a useful linear relationship between typing speed and surface angle. Reject Ho. We have convincing evidence of a useful linear relationship between typing speed and surface angle. Do not reject Ho. We have convincing evidence of a useful linear relationship between typing speed and surface angle. (b) Are the values of s̟ and r² consistent with the conclusion from part (a)? Explain. e and Se show almost no linear relationship between the two variables. No, 2 Yes, r₂ and s show almost no linear relationship between the two variables.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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A paper describes a study to determine the effects of several keyboard characteristics on typing speed. One of the variables considered was the front-to-back surface angle of the keyboard. Minitab output resulting from fitting the simple linear regression model with x = surface angle (degrees) and y typing speed (words per minute) is given below. Regression Analysis: Typing Speed versus Surface Angle = The regression equation is Typing Speed Predictor Constant Surface Angle = 60.0 +0.0036 Surface Angle Coef 60.0286 SE Coef T P 0.00357 0.2466 0.03823 243.45 0.000 0.09 0.931 S = 0.511766 R-Sq = 0.3% R-Sq (adj) = 0.0% Analysis of Variance Source DF SS MS F P Regression 1 0.0023 0.0023 0.01 0.931 Residual 3 0.7857 0.2619 Error Total 4 0.788 (a) Assuming that the basic assumptions of the simple linear regression model are reasonably met, carry out a hypothesis test using α = 0.05 to decide if there is a useful linear relationship between x and y. Calculate the test statistic. (Enter your answer to two decimal places.) Calculate the test statistic. (Enter your answer to two decimal places.) t = What is the P-value for this test? (Enter your answer to three decimal places.) P-value = What can you conclude? Reject Ho. We do not have convincing evidence of a useful linear relationship between typing speed and surface angle. Do not reject Ho. We do not have convincing evidence of a useful linear relationship between typing speed and surface angle. Reject Ho. We have convincing evidence of a useful linear relationship between typing speed and surface angle. Do not reject Ho. We have convincing evidence of a useful linear relationship between typing speed and surface angle. (b) Are the values of s̟ and r² consistent with the conclusion from part (a)? Explain. e and Se show almost no linear relationship between the two variables. No, 2 Yes, r₂ and s show almost no linear relationship between the two variables.
Transcribed Image Text:A paper describes a study to determine the effects of several keyboard characteristics on typing speed. One of the variables considered was the front-to-back surface angle of the keyboard. Minitab output resulting from fitting the simple linear regression model with x = surface angle (degrees) and y typing speed (words per minute) is given below. Regression Analysis: Typing Speed versus Surface Angle = The regression equation is Typing Speed Predictor Constant Surface Angle = 60.0 +0.0036 Surface Angle Coef 60.0286 SE Coef T P 0.00357 0.2466 0.03823 243.45 0.000 0.09 0.931 S = 0.511766 R-Sq = 0.3% R-Sq (adj) = 0.0% Analysis of Variance Source DF SS MS F P Regression 1 0.0023 0.0023 0.01 0.931 Residual 3 0.7857 0.2619 Error Total 4 0.788 (a) Assuming that the basic assumptions of the simple linear regression model are reasonably met, carry out a hypothesis test using α = 0.05 to decide if there is a useful linear relationship between x and y. Calculate the test statistic. (Enter your answer to two decimal places.) Calculate the test statistic. (Enter your answer to two decimal places.) t = What is the P-value for this test? (Enter your answer to three decimal places.) P-value = What can you conclude? Reject Ho. We do not have convincing evidence of a useful linear relationship between typing speed and surface angle. Do not reject Ho. We do not have convincing evidence of a useful linear relationship between typing speed and surface angle. Reject Ho. We have convincing evidence of a useful linear relationship between typing speed and surface angle. Do not reject Ho. We have convincing evidence of a useful linear relationship between typing speed and surface angle. (b) Are the values of s̟ and r² consistent with the conclusion from part (a)? Explain. e and Se show almost no linear relationship between the two variables. No, 2 Yes, r₂ and s show almost no linear relationship between the two variables.
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