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. Output resulting from fitting the simple linear regression model with x = surface angle (degrees) and y typing speed (words per minute) is given below. Reading the output: The Regression Analysis contains the regression equation as a function of x, a column of predictors (Constant is the y-intercept, Surface Angle is the independent variable), Coef is the estimated regression coefficients utilized in the regression equation, SE Coef is the standard error of the Predictor, T is the t-test statistic of the Predictor, P is the p- value of the Predictor), S is the standard error of the estimated model, R-sq is the coefficient of determination. Regression Analysis: Typing Speed versus Surface Angle The regression equation is Typing Speed 60.0+ 0.0036 Surface Angle SE Coef 0.2466 0.03956 Predictor Constant Surface Angle S 0.511766 State the appropriate null and alternative hypothesis. OH: B=0 H₂: B<0 OH: B=0 H: B> 0 OH: B>0 H₂: μ< 0 Coef 60.0284 0.00356 R-Sq 0.2% R-Sq (adj) 0.0% (a) Suppose that the basic assumptions of the simple linear regression model are met. Carry out a hypothesis test using α = 0.05 to decide if there is a useful linear relationship between x and y. Perform the Model Utility Test. O Ho: B<0 H₂: ß> 0 OH: B=0 H: Bao P-value = T 243.45 0.09 P 0.000 0.931 Calculate the test statistic and P-value for this test. (Round your test statistic to two decimal places and your P-value to three decimal places.) t = State the conclusion in the problem context. Owe fail to reject Ho. We do not have convincing evidence of a useful linear relationship between typing speed and surface angle. Owe fail to reject Ho. We have convincing evidence of a useful linear relationship between typing speed and surface angle. O We reject H. We do not have convincing evidence of a useful linear relationship between typing speed and surface angle. O We reject Ho. We have convincing evidence of a useful linear relationship between typing speed and surface angle. b) Are the values of s and r² consistent with the conclusion from part (a)? Explain. No, r₂ and se show almost no linear relationship between the two variables. O No, r₂ and se show a strong linear relationship between the two variables. O Yes, r₂ and se show almost no linear relationship between the two variables. O It is impossible to determine if r2 and se are consistent with the conclusion from part (a). O Yes, r₂ and se show a strong linear relationship between the two variables.

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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. Output resulting from fitting the simple linear regression
model with x = surface angle (degrees) and y = typing speed (words per minute) is given below.
Reading the output: The Regression Analysis contains the regression equation as a function of x, a column of predictors
(Constant is the y-intercept, Surface Angle is the independent variable), Coef is the estimated regression coefficients utilized
in the regression equation, SE Coef is the standard error of the Predictor, T is the t-test statistic of the Predictor, P is the p-
value of the Predictor), S is the standard error of the estimated model, R-sq is the coefficient of determination.
Regression Analysis: Typing Speed versus Surface Angle
The regression equation is
Typing Speed 60.0+ 0.0036 Surface Angle
SE Coef
Predictor
Constant
Surface Angle
S 0.511766
OH: B=0
H: B> 0
State the appropriate null and alternative hypothesis.
OH₁: B=0
H₂: B<0
OHO: B>0
H₂H<0
OHO: B<0
H: ß> 0
Coef
60.0284
0.00356
R-Sq= 0.2% R-Sq (adj) 0.0%
(a) Suppose that the basic assumptions of the simple linear regression model are met. Carry out a hypothesis test using
α = 0.05 to decide if there is a useful linear relationship between x and y. Perform the Model Utility Test.
O H₁: B = 0
H₂: B = 0
0.2466
0.03956
P-value =
T
243.45
0.09
P
0.000
0.931
Calculate the test statistic and P-value for this test. (Round your test statistic to two decimal places and your P-value to
three decimal places.)
t =
State the conclusion in the problem context.
● We fail to reject Ho. We do not have convincing evidence of a useful linear relationship between typing speed and
surface angle.
O We fail to reject Ho. We have convincing evidence of a useful linear relationship between typing speed and surface
angle.
O We reject H
We do not have convincing evidence of a useful linear relationship between typing speed and
surface angle.
O We reject Ho. We have convincing evidence of a useful linear relationship between typing speed and surface
angle.
(b) Are the values of s and r² consistent with the conclusion from part (a)? Explain.
O No, r₂ and se show almost no linear relationship between the two variables.
O No, r₂ and se show a strong linear relationship between the two variables.
O Yes, r₂ and se show almost no linear relationship between the two variables.
O It is impossible to determine if r₂ and se are consistent with the conclusion from part (a).
O Yes, r₂ and se show a strong 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. Output resulting from fitting the simple linear regression model with x = surface angle (degrees) and y = typing speed (words per minute) is given below. Reading the output: The Regression Analysis contains the regression equation as a function of x, a column of predictors (Constant is the y-intercept, Surface Angle is the independent variable), Coef is the estimated regression coefficients utilized in the regression equation, SE Coef is the standard error of the Predictor, T is the t-test statistic of the Predictor, P is the p- value of the Predictor), S is the standard error of the estimated model, R-sq is the coefficient of determination. Regression Analysis: Typing Speed versus Surface Angle The regression equation is Typing Speed 60.0+ 0.0036 Surface Angle SE Coef Predictor Constant Surface Angle S 0.511766 OH: B=0 H: B> 0 State the appropriate null and alternative hypothesis. OH₁: B=0 H₂: B<0 OHO: B>0 H₂H<0 OHO: B<0 H: ß> 0 Coef 60.0284 0.00356 R-Sq= 0.2% R-Sq (adj) 0.0% (a) Suppose that the basic assumptions of the simple linear regression model are met. Carry out a hypothesis test using α = 0.05 to decide if there is a useful linear relationship between x and y. Perform the Model Utility Test. O H₁: B = 0 H₂: B = 0 0.2466 0.03956 P-value = T 243.45 0.09 P 0.000 0.931 Calculate the test statistic and P-value for this test. (Round your test statistic to two decimal places and your P-value to three decimal places.) t = State the conclusion in the problem context. ● We fail to reject Ho. We do not have convincing evidence of a useful linear relationship between typing speed and surface angle. O We fail to reject Ho. We have convincing evidence of a useful linear relationship between typing speed and surface angle. O We reject H We do not have convincing evidence of a useful linear relationship between typing speed and surface angle. O We reject Ho. We have convincing evidence of a useful linear relationship between typing speed and surface angle. (b) Are the values of s and r² consistent with the conclusion from part (a)? Explain. O No, r₂ and se show almost no linear relationship between the two variables. O No, r₂ and se show a strong linear relationship between the two variables. O Yes, r₂ and se show almost no linear relationship between the two variables. O It is impossible to determine if r₂ and se are consistent with the conclusion from part (a). O Yes, r₂ and se show a strong linear relationship between the two variables.
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