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In statistics question 1 of attached image, is the ANOVA table values correct, and does it show model insignificant?

In statistics question 1 of attached image, is the ANOVA table values correct, and does it show model insignificant?

Calculus For The Life Sciences
Calculus For The Life Sciences
2nd Edition
ISBN:9780321964038
Author:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Publisher:GREENWELL, Raymond N., RITCHEY, Nathan P., Lial, Margaret L.
Chapter1: Functions
Section1.2: The Least Square Line
Problem 8E
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In statistics question 1 of attached image, is the ANOVA table values correct, and does it show model insignificant?
Calculations HW6 1) In a regression analysis involving 18 observations and four independent variables, the following information was obtained. Multiple R.6000 R Square= .3600 n = 18 4 independent variables. K=4 Standard Error = 4.8000 a) Based on the above information, fill in all the blanks in the following ANOVA table. b) Is the model significant? No, the model is not significant t the ANOVA df Regression ?K=? ₂1-K-1=1 13 Error Intercept n=31 K=4 2= 0.05x3 Total Error Sum of squares SSE = (std error)² x df = (4.8) ²³ x 13 = error 299.52 168.48 299.52 468 SST = SSE Total Sun of Squares 299.52 (-0.3600=468 Regression 5$ SST = SSR+SSE 468=55R+299.52 SSR=168.48 1-R2 2) Multiple regression analysis was used to study the relationship between a dependent variable, y, and four independent variables; x₁, x2, x3, and x4. The following is a partial result of the regression analysis involving 31 observations. dfreg X1 X2 X4 ANOVA SS 2n-1= (17 Error df Regression K= Total Coefficients 18.00 12.00 24.00 -36.00 16.00 Standard Error 6.00 8.00 MS ASR 42.12 SE 23.04 48.00 36.00 STEM 2.00 SS SSR= MSR-df = 125.4-500125 XSSE= SST-SSR 1 = 760-500= (260) = SST n-k-1=(26) n-1-30 760 MS = MSR F ? 1.828 MSE=SSE/ of E = 260/26 = (10) F-critical Value is df4/13df = 3.1791 MSR MSE =1-828 cats opt F stut = MSR [Fstat= = 42.12 23.04 mean ss MSR=SSR MSE SSE = 2૧૧.52/3 =23.04 a) Compute the multiple coefficient of determination. See attached b) Perform a / test and determine whether or not B₁ is significantly different from zero (a = .05). c) Perform a r test and determine whether or not ß4 is significantly different from zero (a = .05). d) At a = .05, perform an F test and determine whether or not the regression model is significant. MSE = 125 10 dferror =168.48 P-value Excel =FDIST (12.5, 4,26) = 0.0000 4 = 42.12 (12.5)
Transcribed Image Text:Calculations HW6 1) In a regression analysis involving 18 observations and four independent variables, the following information was obtained. Multiple R.6000 R Square= .3600 n = 18 4 independent variables. K=4 Standard Error = 4.8000 a) Based on the above information, fill in all the blanks in the following ANOVA table. b) Is the model significant? No, the model is not significant t the ANOVA df Regression ?K=? ₂1-K-1=1 13 Error Intercept n=31 K=4 2= 0.05x3 Total Error Sum of squares SSE = (std error)² x df = (4.8) ²³ x 13 = error 299.52 168.48 299.52 468 SST = SSE Total Sun of Squares 299.52 (-0.3600=468 Regression 5$ SST = SSR+SSE 468=55R+299.52 SSR=168.48 1-R2 2) Multiple regression analysis was used to study the relationship between a dependent variable, y, and four independent variables; x₁, x2, x3, and x4. The following is a partial result of the regression analysis involving 31 observations. dfreg X1 X2 X4 ANOVA SS 2n-1= (17 Error df Regression K= Total Coefficients 18.00 12.00 24.00 -36.00 16.00 Standard Error 6.00 8.00 MS ASR 42.12 SE 23.04 48.00 36.00 STEM 2.00 SS SSR= MSR-df = 125.4-500125 XSSE= SST-SSR 1 = 760-500= (260) = SST n-k-1=(26) n-1-30 760 MS = MSR F ? 1.828 MSE=SSE/ of E = 260/26 = (10) F-critical Value is df4/13df = 3.1791 MSR MSE =1-828 cats opt F stut = MSR [Fstat= = 42.12 23.04 mean ss MSR=SSR MSE SSE = 2૧૧.52/3 =23.04 a) Compute the multiple coefficient of determination. See attached b) Perform a / test and determine whether or not B₁ is significantly different from zero (a = .05). c) Perform a r test and determine whether or not ß4 is significantly different from zero (a = .05). d) At a = .05, perform an F test and determine whether or not the regression model is significant. MSE = 125 10 dferror =168.48 P-value Excel =FDIST (12.5, 4,26) = 0.0000 4 = 42.12 (12.5)
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