Computer output for fitting a simple linear model is given
below. State the value of the sample slope for this model and give
the null and alternative hypotheses for testing if the slope in the
population is different from zero. Identify the p-value and use it
(and a 5% significance level) to make a clear conclusion about the
effectiveness of the model.
The regression equation is Y=82.0-0.0116X.
Predictor Coef SECoef T P.
Constant 81.98 11.76 6.97 0.000
X -0.01161 0.00968. -1.20 0.245
Sample slope: ?
p-value: ?
Does X appear to be an effective predictor of the
response variable Y?
As per given output
Sample Slope = -0.0116
P-value = 0.245
since P-value > alpha 0.05 so it is not significant
No, X not appear to be an effective predictor of the response variable Y
Computer output for fitting a simple linear model is given below. State the value of the...
Computer output for fitting a simple linear model is given below.State the value of the sample slope for this model and give the null and alternative hypotheses for testing if the slope in the population is different from zero. Identify the p-value and use it (and a 5% significance level) to make a clear conclusion about the effectiveness of the model. The regression equation is Y - 78.8 -0.014. Predictor Coef SE Coef T P Constant 78.79 11.30 6.97 0.000...
Computer output for fitting a simple linear model is given below. State the value of the sample slope for the given model. In testing if the slope in the population is different from zero, identify the p-value and use it (and a 5% significance level) to make a clear conclusion about the effectiveness of the model. Coefficients: Estimate Std.Error t value Pr(>|t|) (Intercept) 821.91 88.38 9.30 0.000 A -3.804 1.247 -3.05 0.006 Sample slope: Enter your answer; sample slope p-value:...
Computer output for fitting a simple linear model is given below. State the value of the sample slope for this model and give the null and alternative hypotheses for testing if the slope in the population is different from zero. Identify the p-value and use it (and a 5% significance level) to make a clear conclusion about the effectiveness of the model.
Chapter 9, Section 1, Exercise 008 Computer output for fitting a simple linear model is given below. State the value of the sample slope for the given model. In testing if the slope in the population is different from zero, identify the p-value and use it (and a 5% significance level) to make a clear conclusion about the effectiveness of the model. Coefficients: Estimate Std.Error t value Pr(>Itl) Intercept) 820.15 88.19 9.30 0.000 -3.616 .186 -3.05 0.006 Sample slope p-value...
JIN - Students 6-3 WileyPLUS: Module Sex Homework - HP.34 Wiley PLUS M LU C Lock, Statistics: Unlocking the Power of Data, 2e Help System Announcements y & Practice Assignment Gradebook ORION Assignment JRCES PRINTER VERSION BACK NEXT Chapter 9, Section 1, Exercise 005 Computer output for fitting a simple linear model is given below. State the value of the sample slope for the given model. In testing if the slope in the population is different from zero, identify the...
Consider the following partial computer output from a simple linear regression analysis. Predictor Coef SE Coef T P 4.8615 9.35 0.5201 0.000 Constant -0.34655 0.05866 Independent Var S = .4862R-Sq| Analysis of Variance SS MS Source DF F Regression 1 34.90 Residual Error 13 Total 14 11.3240 Calculate the MSE Consider the following partial computer output from a simple linear regression analysis. Predictor Coef SE Coef T P 4.8615 9.35 0.5201 0.000 Constant -0.34655 0.05866 Independent Var S = .4862R-Sq|...
Consider the following partial computer output from a simple linear regression analysis. P Predictor Coef SE Coef T Constant 9.35 0.000 4.8615 0.5201 0.05866 Independent Var -0.34655 S=4862R-Sq. Analysis of Variance MS DF SS F Source 1 34.90 Regression 13 Residual Error 14 11.3240 Total What is the predicted value of ywhen x 9.00?
Chapter 9, Section 1, Exercise 002 Use the computer output to estimate the intercept β0 and the slope β- The regression equation is Y 823 - 3.67X. Predictor Coef SE Coef Constant 822.899 89.45 9.20 0.000 -3.674 1.205-3.05 0.006 intercept β0 : Slope 1 We were unable to transcribe this imageChapter 9, Section 1, Exercise 006 tem ute autput a rting a simpla inir medal gi en elo Th2 regressor cquation Y = 81.8-0.0151x. State :he walua af the Sandle...
Chapter 9, Section 1, Exercise 001 Use the computer output to estimate the intercept beta Subscript 0 and the slope beta Subscript 1. The regression equation is Upper Y equals 24.0 plus 4.89 Upper X. Predictor Coef SE Coef T P Constant 24.038 5.192 4.63 0.000 Upper X 4.886 0.7358 6.64 0.000 Intercept beta Subscript 0 Baseline colon Slope beta Subscript 1 Baseline colon
Suppose we have data on the number of U.S. recruits who were rejected for service in a war against Spain because they did not have enough teeth. We wish to compare the rejection rate for recruits who were under the age of 20 with the rate for those who were 40 or over. To run a logistic regression for this setting, we define an indicator explanatory variable x with values 0 for age under 20 and 1 for age 40...