Use the following ANOVA table for regression to answer the questions.
Analysis of Variance
Source | DF | SS | MS | F | P |
Regression | 1 | 289.0 | 289.0 | 2.01 | 0.158 |
Residual Error | 174 | 25021.2 | 143.8 | ||
Total | 175 | 25310.2 |
Give the F-statistic and p-value.
Enter the exact answers.
The F-statistic is .
The p-value is
Choose the conclusion of this test using a 5% significance
level.
Do not reject H0. We did not find evidence that the model is effective. |
Reject H0. The model is not effective. |
Reject H0. The model is effective. |
Do not reject H0. We did not find evidence that the model is not effective. |
The F-statistic is =2.01
The p-value is = 0.158
P value > 0.05
Do not reject H0. We did not find evidence that the model is effective.
Use the following ANOVA table for regression to answer the questions. Analysis of Variance Source DF...
Use the following ANOVA table for regression to answer the questions. Analysis of Variance Source DF SS MS F P Regression 1 3404.5 3404.5 22.3 0.000 Residual Error 174 26569.8 152.7 Total 175 29974.3 Give the F-statistic and p-value. Enter the exact answers. The F-statistic is ? The p-value is ? Choose the conclusion of this test using a 5% significance level. Reject H0. The model is effective. Do not reject H0. We did not find evidence that the model...
Consider the ANOVA table that follows. Analysis of Variance Source DF SS MS F Regression 5 3,931.60 786.32 14.34 Residual Error 50 2,742.06 54.84 Total 55 6,673.66
The following table is the output of multiple linear regression analysis. a. Use the table to report the F statistic. What is its degree of freedom? What is the number of observations. b. Find the p-value related to F on the computer output and report its value. Using the p-value, test the significance of the regression model at the .10, .05, .01, and .001 levels of significance. What do you conclude? Please show work and explain each step! df ANOVA...
Use the table below to answer the following questions. Source df SS MS p-value A 1 1.36 1.360 0.266 B 1 0.622 0.622 0.451 AB 1 22.405 22.405 0.000 Error 132 143.948 1.091 x Total 135 168.335 x x a) How many levels (a) are there for factor A? b) How many levels (b) are there for factor B? 1) Test for treatment effect α=0.05 H0: No treatment effect vs Ha: There is some treatment effect F= Reject H0...
The following ANOVA table is from a multiple regression analysis: MS F Source Regression Error Total df 5 25 SS 2000 2500 The observed F value is __ O 20 O 400 O 2000 O 500 O 10
Chapter 9, Section 2, Exercise 032 Use the following ANOVA table for regression to answer the questions. Response: Y Source DF Sum Sq Mean Sq F-value Pr(>F) Regression 1 354.12 354.12 13.84 0.000 Residual Error 359 9186.81 25.59 Total 360 9540.93 Give the F-statistic and p-value. Enter the exact answers. The F-statistic is The p-value is
ANOVA df SS Regression 1 882 Residual 20 4000 Total 21 4882 Coefficients Standard Error t Stat Intercept 5.00 3.56 Variable x 6.30 3.00 Use the ANOVA table that was provided in question 7 and Perform an F test and determine whether x and y are related. Use α = .05 Answer Options: Since the test statistic F = 3.45 < 4.35 ,Fail to reject HO Since the test statistic F = .45< 3.45, Fail to reject HO Since the...
Refer to the following ANOVA table. Source DF SS MS F Regression 4 34 8.5 5.06 Error 25 42 1.68 Total 29 76 Compute the coefficient of multiple determination. Multiple Choice 0.810 0.16 0.447 0.382
You may need to use the appropriate technology to answer this question. In a regression analysis involving 27 observations, the following estimated regression equation was developed. ŷ = 25.2 + 5.5x1 For this estimated regression equation SST = 1,550 and SSE = 550. (a) At α = 0.05, test whether x1 is significant. State the null and alternative hypotheses. H0: β1 = 0 Ha: β1 ≠ 0H0: β0 = 0 Ha: β0 ≠ 0 H0: β1 ≠ 0 Ha: β1...
given the following anova table: source DF SS MS F Regression 1 1,050.0 1,050.0 28.00 error 14 525.0 37.50 total 15 1,575.0 A. determine the coefficient of determination B. assuming a direct relationship between the variables, what is the correlation coefficient? C. determine the standard error of estimate