PLS SHOW ALL CALCULATIONS AND EXPLAIN YOUR ANSWERS. THANK YOU!!! A security anal

Question

PLS SHOW ALL CALCULATIONS AND EXPLAIN YOUR ANSWERS. THANK YOU!!!

A security analyst specializing in the stocks of the motion picture industry wants to determine the relationship between the number of movie theater tickets sold in December and 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 years 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 anser. Also, sales of mocie tickets in December are expected to be aprrox. 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 improving the current recommendation for the motion picture industry? Explain how you might do so.

Explanation / Answer

According to Thomas and Maurice a regression analysis is a statistical technique for estimating the parameters of an equation and testing for statistical significance. The regression analysis is a technique used to determine the mathematical relation between dependent variable and one or more explanatory variable. The explanatory variable is the variable that causes the dependent variable to take a different value. We use the simple linear regression model: Y=a+bX or with our problem E = a + bN, where E is the total earnings and N is the number of tickets sold in Dec. We would take E – total earnings of the motion picture industry per year , N – number of tickets sold in December (950,000), a – parameter estimate (25,042,000), b – parameter estimate (32.31). E=25042000 + 32.31 * 950000 E=25042000+30694500 E=55736500 The earnings for the year would be expected to be 55736500. Because the December month will account for 48000000 then this means that 86% of the industries earnings will come from the ticket sales in that Month. Once we calculate the regression analysis we must the parameters of an equation are estimated, the analyst must address the question of whether the parameter estimates (aˆ and bˆ) are significantly different from 0. (Thomas & Maurice, 2011). We use a t-test to determine statistically how large bˆ must be in order to conclude that b is not equal to 0. We use a t-ratio: t=bˆ/Sbˆ, where b is equal to the parameter estimate and Sb is equal to the standard error t = 32.31 / 8.54 t = 3.78. We would next look at the critical value for t, according to text is 2.160. 3.78 is greater than 2.160 so this means that the sales in Dec. are significant to the overall sales for the year.

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