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UMMARY OUTPUT Dependent Variable: Home Video Units (Thousands) Regression Statistics Multiple R 0.8964 R square 0.8036 Adjusted R Square 0.8023 Standard Error 526.93 Observations 148
UMMARY OUTPUT Dependent Variable: Home Video Units (Thousands) Regression Statistics Multiple R 0.8964 R square 0.8036 Adjusted R Square 0.8023 Standard Error 526.93 Observations 148 ANOVA df SS MS F Significance F Regression 1 1.66E+08 1.66E+08 597.41 0.0000 Residual 146 4.05E+07 2.78E+05 Total 147 2.06E+08 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 71.92 66.77 1.08 0.2832 -60.04 203.87 Gross Box Office ($ Millions) 19.45 0.80 24.44 0.0000 17.88 21.02
UMMARY OUTPUT | ||||||
---|---|---|---|---|---|---|
Dependent Variable: Home Video Units (Thousands) | ||||||
Regression Statistics | ||||||
Multiple R | 0.8964 | |||||
R square | 0.8036 | |||||
Adjusted R Square | 0.8023 | |||||
Standard Error | 526.93 | |||||
Observations | 148 | |||||
ANOVA | ||||||
df | SS | MS | F | Significance F | ||
Regression | 1 | 1.66E+08 | 1.66E+08 | 597.41 | 0.0000 | |
Residual | 146 | 4.05E+07 | 2.78E+05 | |||
Total | 147 | 2.06E+08 | ||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |
Intercept | 71.92 | 66.77 | 1.08 | 0.2832 | -60.04 | 203.87 |
Gross Box Office ($ Millions) | 19.45 | 0.80 | 24.44 | 0.0000 | 17.88 | 21.02 |
Is the relationship between gross box office sales and home video units significant? How can you tell? Do you think the linear model is the best fit for the relationship? Why or why not?
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