i. Use MS Excel Data Analysis ToolPak to perform a multiple regression analysis using Quality as the response variable and Helpfulness and Clarity as the explanatory variables. Write down the corresponding coefficient estimates and provide the regression output.

j. Perform an F-test for the overall usefulness of the model in part i) using a 5% significance level. Make sure you follow all the steps for hypothesis testing indicated in the Instructions section and clearly state your conclusion.

k. Test manually if the Clarity variable is significant in the model in part i). Make sure you follow all the steps for hypothesis testing indicated in the Instructions section and clearly state your conclusion.

l. Using the adjusted R² criterion, does including Clarity as an additional predictor variable improve the model in part i)? Explain why it is better to use the adjusted R² over the R² to determine if the addition of this new variable improves the model.

Regression Statistics			ANOVA
Multiple R	0.998544859			df	SS	MS	F	Significance F
R Square	0.997091836		Regression	2	255.2639136	127.6319568	62229.00058	0
Adjusted R Square	0.997075813		Residual	363	0.744514614	0.002051004
Standard Error	0.045288017		Total	365	256.0084282
Observations	366
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	-0.020353502	0.010520921	-1.934574223	0.0538193	-0.04104311	0.000336106	-0.04104311	0.000336106
helpfulness	0.538358378	0.007216008	74.60611907	2.8925E-222	0.524167949	0.552548808	0.524167949	0.552548808
clarity	0.465505241	0.00707634	65.78333849	8.6445E-204	0.451589474	0.479421009	0.451589474	0.479421009