Basic Estimating – Week 2
A security analyst specializing in the stocks of the motion picture industry the relation between the number of movie theater tickets sold in December and the annual level of earnings in the motion picture industry. Time-series data for the last 15 years are used to estimate the regression model. E = a + bN where E is total earnings of the motion picture industry measured in dollars per year and N is the number of tickets sold in December. The regression output is as follows:
DEPENDENT VARIABLE: E
R-SQUARE
F-RATIO
P-VALUE ON F
OBSERVATIONS: 15
0.8311
63.96
0.0001
VARIABLE
PARAMETER ESTIMATE
STANDARD ERROR
T-RATIO
P-VALUE
INTERCEPT
25042000.00
20131000.00
1.24
0.2369
N
32.31
8.54
3.78
0.0023
How well do movie ticket sales in December explain the level of earnings for the entire year? Present statistical evidence to support your answer. Also, sales of movie tickets in December are expected to be approximately 950,000. According to this regression analysis, what do you expect earnings for the year to be? Prior to this analysis, the estimate for annual earnings is $48 million. Is this evidence strong enough for you to consider a improving the current recommendation for the motion picture industry? Explain. Respond to at least two of your fellow students’ postings
Basic Estimating - Week 2
A security analyst specializing in the stocks of the motion picture industry the relation between the number of movie theater tickets sold in December and the annual level of earnings in the motion picture industry. Time-series data for the last 15 years are used to estimate the regression model. E = a + bN where E is total earnings of the motion picture industry measured in dollars per year and N is the number of tickets sold in December. The regression output is as follows:
DEPENDENT VARIABLE: E R-SQUARE F-RATIO P-VALUE ON F
OBSERVATIONS: 15 0.8311 63.96 0.0001
VARIABLE PARAMETER ESTIMATE STANDARD ERROR T-RATIO P-VALUE
INTERCEPT 25042000.00 20131000.00 1.24 0.2369
N 32.31 8.54 3.78 0.0023
How well do movie ticket sales in December explain the level of earnings for the entire year? Present statistical evidence to support your answer. Also, sales of movie tickets in December are expected to be approximately 950,000. According to this regression analysis, what do you expect earnings for the year to be? Prior to this analysis, the estimates for earnings in December are $48 million. Is this evidence strong enough for you to consider a improving the current recommendation for the motion picture industry? Explain.
To determine how well movie ticket sales in December explain the level of earnings for the entire year, we can look at the R-squared value in the regression output. The R-squared value measures the proportion of the variation in the dependent variable (earnings) that can be explained by the independent variable (number of tickets sold in December). In this case, the R-squared value is 0.8311, which means that approximately 83.11% of the variation in earnings can be explained by the number of tickets sold in December.
The F-ratio in the regression output is also relevant for assessing how well the independent variable explains the dependent variable. The F-ratio tests the overall significance of the regression model. In this case, the F-ratio is 63.96, with a p-value of 0.0001. The p-value is below the typical significance level of 0.05, indicating that the regression model is statistically significant. Therefore, there is strong statistical evidence to support the claim that movie ticket sales in December explain the level of earnings for the entire year.
To estimate earnings for the year based on the regression analysis, we can plug in the expected number of tickets sold in December (950,000) into the regression equation. Using the parameter estimates from the regression output, the expected earnings can be calculated as follows:
E = a + bN
E = 25042000.00 + 32.31 * 950,000
E ≈ $30,819,950,000
According to this regression analysis, the expected earnings for the year would be approximately $30,819,950,000.
Comparing this estimate to the prior estimate of $48 million, there is a significant difference. It is important to consider the evidence strength before making any recommendations. In this case, the regression analysis provides strong statistical evidence that movie ticket sales in December are a significant predictor of earnings for the entire year, as indicated by the high R-squared value and the statistically significant F-ratio. However, since the expected earnings based on the regression analysis are much higher than the prior estimate, this discrepancy may raise questions about the accuracy and reliability of the regression model. Further analysis and consideration of other factors would be necessary before making any conclusions or recommendations.