SUMMARY OUTPUT
Regression Statistics
Multiple R	0.873
R Square	0.762
Adjusted R Square	0.751
Standard Error	0.193
Observations	22
ANOVA
	df	SS	MS	F	Significance F
Regression	1	2.386706774	2.38670677	64.174423	1.1414E-07
Residual	20	0.743818693	0.03719093
Total	21	3.130525467
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%
Intercept	-0.624	0.236	-2.645	0.016	-1.116	-0.132
log tweet rate	0.811	0.101	8.011	0.000	0.599	1.022

Question 10

Use the following information for Questions 10 - 12.

Marketers are interested in how social media can influence prospective consumers of their products. Researchers investigated whether the volume of chatter on twitter (Tweet Rate measured as average of tweets per hour) could be used to predict box office revenue of movies (Box Office Revenue in millions of $).

The regression output is given in the sheet named "Q 10-12".

What is the regression equation to predict Box Office Revenue from Tweet Rate? Use values from the regression output (answers to three decimal places).