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: Enter your answer; p-value
Is the model effective?
Choose the answer from the menu; Is the model
effective?
YesNo
Sample slope : -3.804
P value = 0.006
P value <0.05
Therefore, model is effective.
Yes
Computer output for fitting a simple linear model is given below. State the value of the...
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...
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 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...
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.
Question 7 Find a 95% confidence interval for the slope of the model below with n 30. Coefficients: Estimate Std.Error t value Pr(>It) (Intercept 7.535 1.208 6.24 0.000 0.4633 0.2618 -1.77 0.087 Dose Round your answers to three decimal places. to
Find a 95% confidence interval for the slope of the model below with n = 30. Coefficients: Estimate Std.Error t value Pr>It|) (Intercept) 7.796 -0.4027 1.249 0.2275 6.24 -1.77 0.000 0.087 Dose Round your answers to three decimal places. to i
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...
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...
(d) Write down the fitted simple linear regression model (equation) and discuss its merits using the following output. Consider the intercept, slope, overall goodness of model etc. when commenting. (Note that, in Excel, the time variable begins at Year 1900, i.e. 01/01/1900, 12am). [4 marks] Intercept X Variable 1 Coefficients -164070 5.736757 Standard Error t Stat P-value 28361.13278 -5.785021448 1.64E-06 0.749106082 7.65813654 6.68E-09 Lower 95% Upper 95% -221706.5175 -106433.01 4.214389946 7.2591234
Below you are given a partial computer output based on a sample of fifteen (15) observations. ANOVA df SS Regression 1 50.58 Residual Total 14 106.00 Coefficients Standard Error t Stat p-value Intercept 16.156 1.42 0.0000 Variable x -0.903 0.26 0.0000 The coefficient of determination is. 0.5228 0.4772 0.6535 0.3465