Dependent Variable	Independent Variable
Axis	Y	X
Title	Sales ($100k)	Payroll ($100k)
	5.5	3
	8	6
	4	3
	6	2
	12	8
	9.5	5
Results
	SUMMARY OUTPUT
	Regression Statistics
	Multiple R	0.8908769
	R Square	0.793661651
	Adjusted R Square	0.742077063
	Standard Error	1.489341215
	Observations	6
	ANOVA
		df	SS	MS	F	Significance F
	Regression	1	34.12745098	34.12745098	15.38563536	0.017212066
	Residual	4	8.87254902	2.218137255
	Total	5	43
		Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
	Intercept	2.294117647	1.459846389	1.571478797	0.191168664	-1.759065715	6.347301009
	Payroll ($100k)	1.156862745	0.294933509	3.922452722	0.017212066	0.337996048	1.975729442
	Questions to interpret the results of the regression analysis	Type answer in the box
	1. Is the regression model statistically significant (Yes or No)?
	2. Highlight the cell in green that corresponds to the statistic value you used to answer question #1.
	3. For each unit increase in Payroll, how much do Sales change?
	4. How much variability (in %) in Sales, can be explained by the regression model with Payroll as the independent variable?
	5. Highlight the cell in blue that corresponds to the statistic value you used to answer question #4.
	6. What is the projected Sales (in $100k) when the Payroll is $0?
	7. Highlight the cell in yellow that correponds to the Correlation Coefficient.
	8. If the Payroll ($100k) is 5, what are the estimated Sales ($100k)?