Question

g. Use MS Excel Data Analysis ToolPak to perform a multiple regression analysis using Quality as the response variable and Helpfulness, Clarity, Easiness, and raterInterest as the explanatory variables. Write down the resulting regression equation and provide the regression output.

h. Based on the regression output in part g), which variable(s) seem to be significant predictors of Quality? Which variable(s) do you suggest removing from the model in part g)? Explain why.

Regression Statistics			ANOVA
Multiple R	0.998557685			df	SS	MS	F	Significance F
R Square	0.997117451		Regression	4	255.2704714	63.81761786	31218.84669	0
Adjusted R Square	0.997085512		Residual	361	0.737956795	0.002044202
Standard Error	0.045212848		Total	365	256.0084282
Observations	366
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	-0.029311967	0.015907585	-1.842640924	0.066201252	-0.060595142	0.001971207	-0.060595142	0.001971207
helpfulness	0.535482142	0.007432082	72.05008101	2.4621E-216	0.520866528	0.550097756	0.520866528	0.550097756
clarity	0.464782587	0.007113819	65.33517314	4.3494E-202	0.450792856	0.478772318	0.450792856	0.478772318
easiness	0.006623357	0.003701065	1.78958135	0.074359339	-0.000654999	0.013901713	-0.000654999	0.013901713
raterInterest	0.000357184	0.004873272	0.073294438	0.941612411	-0.009226385	0.009940752	-0.009226385	0.009940752

Answer 1

regression equation is

-0.023+0.535*helpfulness+0.464*clarity+0.0066*easiness+0.0003*raterinterest

based on the individual t test we decide the significance of each variable if the p value is less than 0.05 then the variabke is significant

The significant variables are Helpfulness,  Clarity,

we will remove those variables which are not significant which are Easiness, and raterInterest.

because their p value is > 0.05