SOLUTION: Budget ($) in millions - Gross($)in millions .25 - 12.006 .325 - 47 3.9 - 198.571 6 - 181.28 6.4 - 36.9 8 - 107.93 10 - 138.339 12 260 15 - 103.001 17 - 72.219 18.5

SOLUTION: Budget ($) in millions - Gross($)in millions .25 - 12.006 .325 - 47 3.9 - 198.571 6 - 181.28 6.4 - 36.9 8 - 107.93 10 - 138.339 12 260 15 - 103.001 17 - 72.219 18.5 - 81

Question 581280: Budget ($) in millions - Gross($)in millions
.25 - 12.006
.325 - 47
3.9 - 198.571
6 - 181.28
6.4 - 36.9
8 - 107.93
10 - 138.339
12 260
15 - 103.001
17 - 72.219
18.5 - 81.843
20 - 242.374
22 - 217.631
25 - 96.067
35 - 56.876
39 - 197.171
45 - 20.1
50 - 147.54
50 - 48.265
55 - 68.75
A) BRIEFLY CHARACTERIZE THE CORRELATION COEFFICIENT
B) THE EQUATION OF THE REGRESSION LINE CALCULATED ON THESE VALUES IS GROSS INCOME= 123.44-.536 BUDGET. USE THE REGRESSION LINE TO PREDICT THE GROSS INCOME FOR A MOVIE WITH BUDGET 30 MILLION DOLLARS
C) EXPLAIN WHETHER OR NOT YOU THINK THIS IS A REASONABLE PREDICTION. please help me!
Answer by KMST(5328) (Show Source): You can put this solution on YOUR website!
A) Your correlation coefficient is so small that there is no correlation (I got ). Obviously gross income does not depend on budget. In other words, you cannot expect to improve gross income by manipulating budget. Budget seems to have no effect.
B) The equation predicts that a lower budget movie will produce greater gross income. I got a slightly different regression line, but with x=30 (for a $30,000,000 budget), the equation you have gives you
y(30)=123.44-0.536(30)=107.36, predicting a gross income of $107,360,000.
C) Because the correlation coefficient is so small, and the slope is so flat, the regression line has no predictive ability. I don't think anyone would use a trendline with a correlation coefficient of less tan 0.5 to predict anything, and a flat slope says y does not depend on x, anyway.
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