6. (a) The scatterplot is:
The output is:
r² | 0.853 | |||||
r | 0.924 | |||||
Std. Error | 78.138 | |||||
n | 7 | |||||
k | 1 | |||||
Dep. Var. | Gross | |||||
ANOVA table | ||||||
Source | SS | df | MS | F | p-value | |
Regression | 1,77,287.3737 | 1 | 1,77,287.3737 | 29.04 | .0030 | |
Residual | 30,527.4835 | 5 | 6,105.4967 | |||
Total | 2,07,814.8571 | 6 | ||||
Regression output | confidence interval | |||||
variables | coefficients | std. error | t (df=5) | p-value | 95% lower | 95% upper |
Intercept | -135.8573 | |||||
Budget | 3.1161 | 0.5783 | 5.389 | .0030 | 1.6296 | 4.6026 |
1. The hypothesis being tested is:
H0: There is no relationship between the Budget and Gross.
Ha: There is a relationship between the Budget and Gross.
2. r = 0.924
3. t = 5.389
4. p-value = 0.0030
5. Since the p-value (0.0030) is less than the significance level (0.05), we can reject the null hypothesis.
Therefore, we have sufficient evidence to conclude that there is a relationship between the Budget and Gross.
6. From the 95% confidence interval, we have sufficient evidence to conclude that there is a relationship between the Budget and Gross.
7. r² = 0.853
It means that 85.3% of the variability in Gross is explained by the Budget.
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