Academic Integrity: tutoring, explanations, and feedback — we don’t complete graded work or submit on a student’s behalf.

TOTALS: (m) Give an equation for and calculate the Fstatistic in the ANOVA test

ID: 3239146 • Letter: T

Question

TOTALS:

(m) Give an equation for and calculate the Fstatistic in the ANOVA test of H(there is no linear relationship between x & y) versus H(there exists a linear relationship between x & y). Calculate the degrees of freedom df for this Fstatistic. Use Excel to calculate the corresponding pvalue. (n) Give an equation for and calculate the estimated standard deviation of the slope s(b). (o) Give an equation for and calculate the tstatistic to test H( = 0) vs H( 0). Calculate the degrees of freedom for this tstatistic. Use Excel to calculate the corresponding pvalue. (p) Write the sample regression equation again in the following format: y = b + bx (tstatistic)*** n = ?; r² = ?; r²(adj) = ?; F = ? [pvalue] This format is typically presented in a report’s main text. In addition, the corresponding table of full regression results can be put in the appendix. For the number of stars besides the tstatistic, use this rule: *** for pvalue 0.01; ** for 0.01< pvalue 0.05; * for 0.05 < pvalue 0.1.

obs x y x^2 xy 1 6.95 8.56 48.30250 59.49200 2 4.70 6.71 22.09000 31.53700 3 5.13 9.67 26.31690 49.60710 4 8.67 5.63 75.16890 48.81210 5 2.48 8.52 6.15040 21.12960 Total 27.93000 39.09000

Explanation / Answer

F=1.0656

p=0.377

p>0.05

Fail to reject Null hypotehsis

ACcept null hypothesis

there is sufficient evidence to conclude

there is no linear relationship between x & y

Model is not significant

regression equation is

y=9.792-0.3534x

slope=-0.3534

y intercept=9.792

r=0.512

correlation coeffcient=r=0.512

moderate positive relationship exists between x and y.

r sq=0.2621=26.21% variation in y is explained by model.

not a good model

t=-1.0323

SUMMARY OUTPUT Regression Statistics Multiple R 0.511966 R Square 0.262109 Adjusted R Square 0.016146 Standard Error 1.606155 Observations 5 ANOVA df SS MS F Significance F Regression 1 2.749077 2.749077 1.065643 0.377861 Residual 3 7.739203 2.579734 Total 4 10.48828 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 9.792092 2.042775 4.793525 0.017271 3.29107 16.29311 x -0.3534 0.342342 -1.0323 0.377861 -1.44289 0.736086