12.10 FORECASTING MOVIE REVENUES WITH TWITTER. Refer to the IEEE International Conference on Web Intelligence and Intelligent Agent Technology (2010) study on using the volume of chatter on Twitter.com to forecast movie box office revenue, Exercise 11.27 (p. 642). Recall that opening weekend box office revenue data (in millions of dollars) were collected for a sample of 24 recent movies. In addition to each movie's tweet rate, i.e., the average number of tweets referring to the movie per hour 1 week prior to the movie's release, the researchers also computed the ratio of positive to negative tweets (called the PN-ratio). a. Give the equation of a first-order model relating revenue (y) to both tweet rate (x₁) and PN-ratio (x₂). b. Which ß in the model, part a, represents the change in revenue (y) for every 1-tweet increase in the tweet rate (₁), holding PN-ratio (2) constant? c. Which 3 in the model, part a, represents the change in revenue (y) for every 1-unit increase in the PN-ratio (x2), holding tweet rate (x₁) constant? d. The following coefficients were reported: R² .945 and R2 = .940. Give a practical interpretation for both R² and R². e. Conduct a test of the null hypothesis, Ho: ß₁ = ß₂ = 0. Use a = .05. f. The researchers reported the p-values for testing Ho: B₁ = 0 and Ho: B₂ = 0 as both less than .0001. Interpret these results (use a = = .01).
12.10 FORECASTING MOVIE REVENUES WITH TWITTER. Refer to the IEEE International Conference on Web Intelligence and Intelligent Agent Technology (2010) study on using the volume of chatter on Twitter.com to forecast movie box office revenue, Exercise 11.27 (p. 642). Recall that opening weekend box office revenue data (in millions of dollars) were collected for a sample of 24 recent movies. In addition to each movie's tweet rate, i.e., the average number of tweets referring to the movie per hour 1 week prior to the movie's release, the researchers also computed the ratio of positive to negative tweets (called the PN-ratio). a. Give the equation of a first-order model relating revenue (y) to both tweet rate (x₁) and PN-ratio (x₂). b. Which ß in the model, part a, represents the change in revenue (y) for every 1-tweet increase in the tweet rate (₁), holding PN-ratio (2) constant? c. Which 3 in the model, part a, represents the change in revenue (y) for every 1-unit increase in the PN-ratio (x2), holding tweet rate (x₁) constant? d. The following coefficients were reported: R² .945 and R2 = .940. Give a practical interpretation for both R² and R². e. Conduct a test of the null hypothesis, Ho: ß₁ = ß₂ = 0. Use a = .05. f. The researchers reported the p-values for testing Ho: B₁ = 0 and Ho: B₂ = 0 as both less than .0001. Interpret these results (use a = = .01).
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
Please do only the last two parts

Transcribed Image Text:Regression Equation
Revenue (millions) = 1.15 +0.07877 TweetRate
Coefficients
Term
Constant
TweetRate 0.07877 0.00794
Coef SE Coef
1.15
3.68
Model Summary
95% CI
(-6.49, 8.80)
(0.06226, 0.09527)
13.3165 82.42%
T-Value P-Value VIF
0.757
0.000 1.00
0.31
9.92
S R-sq R-sq(adj) PRESS R-sq(pred) AICC
81.59% 7096.95
BIC
66.50% 189.54 191.68
--

Transcribed Image Text:12.10 FORECASTING MOVIE REVENUES WITH TWITTER.
Refer to the IEEE International Conference on Web Intelligence and
Intelligent Agent Technology (2010) study on using the volume of
chatter on Twitter.com to forecast movie box office revenue,
Exercise 11.27 (p. 642). Recall that opening weekend box
office revenue data (in millions of dollars) were collected for a
sample of 24 recent movies. In addition to each movie's tweet
rate, i.e., the average number of tweets referring to the movie
per hour 1 week prior to the movie's release, the researchers
also computed the ratio of positive to negative tweets (called the
PN-ratio).
a. Give the equation of a first-order model relating
revenue (y) to both tweet rate (x₁) and PN-ratio (x₂).
b. Which in the model, part a, represents the change in
revenue (y) for every 1-tweet increase in the tweet rate
(1), holding PN-ratio (x2) constant?
c. Which ß in the model, part a, represents the change in
revenue (y) for every 1-unit increase in the PN-ratio
(x2), holding tweet rate (x₁) constant?
d. The following coefficients were reported: R² = .945 and
R2 = .940. Give a practical interpretation for both R2²
and R²₂.
e. Conduct a test of the null hypothesis, Ho: B₁ B₂ = 0.
=
Use a =
.05.
f. The researchers reported the p-values for testing
Ho: B₁0 and Ho: B2 = 0 as both less than .0001.
=
Interpret these results (use a = = .01).
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