Question

Suppose we want to use Twitter activity to predict box office receipts on the opening weekend for movies. Assuming a linear relationship, the Excel output for this regression model is given below.

                                  

Excel output:

SUMMARY OUTPUT
Regression Statistics
Multiple R	0.9879
R Square	0.9760
Adjusted R Square	0.9712
Standard Error	1830.236
Observations	7
ANOVA
	df	SS	MS	F	Significance F
Regression	1	6.81E+08	6.81E+08	203.153	3.06E-05
Residual	5	16748821	3349764
Total	6	6.97E+08
	Coefficients	Standard Error	t Stat	P-value	Lower 95%	Upper 95%	Lower 95.0%	Upper 95.0%
Intercept	6808.105	854.968	7.962991	0.000504	4610.339	9005.87	4610.339	9005.87
Twitter Activity	0.0503	0.00353	14.25318	3.06E-05	0.041205	0.059338	0.041205	0.059338

(a) State the regression equation for this problem.

(b) Interpret the meaning of b₀ and b₁ in this problem.

(c) Predict the box office receipts on the opening weekend for a movie that has a Twitter activity of 110,000.

(d) At the 0.05 level of significance, is there evidence of a linear relationship between the Twitter activity and the box office receipts on the opening weekend for a movie?

(e) Construct a 95% confidence interval estimate of the population slope β₁. Interpret the confidence interval estimate.

(f) How useful do you think this regression model is for predicting the box office receipts on the opening weekend for a movie?

Answer 1