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All questions are attached, the first three questions do not need to be done. Only questions after the data attachment is mentioned with a youtube video. Thank you for your help!

Data ObservationActual dataTransformed data Number of Tickets SoldTicket PriceNumber of Tickets SoldTicket Price 184254.433.22 2105.9164.662.77 3135.3144.912.64 4107.3184.682.89 5141.3114.952.40 675204.323.00 796.2194.572.94 8124.1134.822.56 996.4154.572.71 1084.9204.443.00 11135.8114.912.40 12111.9174.722.83 1384.2164.432.77 14129.4114.862.40 15115.8144.752.64 1689.3234.493.14 1779.9174.382.83 1883.8224.433.09 1971.1244.263.18 20121.9164.802.77 2174.2244.313.18 22105.6144.662.64 2396.8194.572.94 24108.9144.692.64 2575.8234.333.14 2665.2274.183.30 2763234.143.14 2896214.563.04 29129.9144.872.64 30128.5114.862.40 3191.8164.522.77 3271.9204.283.00 3394.1184.542.89 34118.1174.772.83 35118.2144.772.64 3695.7164.562.77 3774.8194.312.94 38121.6134.802.56 3992.2184.522.89 4086.6244.463.18 41148.6115.002.40 4260.4244.103.18 43142.9134.962.56 4494.5204.553.00 45148.7115.002.40 46129.4134.862.56 4784.8244.443.18 4880.3204.393.00 4941.6263.733.26 5094.1184.542.89 5163.8204.163.00 52111.4144.712.64 5396.2164.572.77 54140.5114.952.40 5599.3194.602.94 56144.3114.972.40 5745.6253.823.22 58159.4105.072.30 5959.4234.083.14 60102.3144.632.64 61139.2144.942.64 6273.1264.293.26 6363.3234.153.14 6469.1274.243.30 65128.2124.852.48 66105.1164.652.77 6763.1234.143.14 68107.3164.682.77 6999.8204.603.00 7090.8224.513.09 71145.6124.982.48 72123.9164.822.77 7373.7234.303.14 7443.1263.763.26 75144.9134.982.56 76130.8124.872.48 7793.5214.543.04 7869254.233.22 7998204.583.00 80137.3114.922.40 8175.7244.333.18 8280.6244.393.18 8376.6254.343.22 84136.9144.922.64 85119.3154.782.71 86117.7124.772.48 87116124.752.48 8895.1164.552.77 89132.3114.892.40 9078.1234.363.14 91113.3144.732.64 92114.6174.742.83 93116.7174.762.83 9486.6204.463.00 95156.1105.052.30 9662.1224.133.09 9798.7174.592.83 98124.3124.822.48 9985.3234.453.14 100162.3115.092.40 MBAE 6865-001 Economic Decisions for Managers (Fall 2021, A2) Group Assignment #2 Due at 11:59 PM, Monday November 1, 2021 1. Analysts at a digital marketing firm collected data on the firm’s extent of website analysis (X), along with the cost per customer (C), and the ad revenue per customer (R). Using regression analysis, the analysts produced the following two outputs: C regressed on ???? R regressed on ?? and ???? Coefficients Standard Error t-Statistic P-Value Lower 95% Upper 95% Intercept 24.598 9.092 2.706 0.008 6.594 42.602 ?? 11.092 1.323 8.384 1.3E-13 8.472 13.712 ??2 −0.100 0.044 −2.274 0.025 −0.188 −0.013 Table Summary: Table divided into seven columns summarizes R regressed on X and X squared. Column 1 notes intercept, X and X squared. The column headers from 2 to 7 are marked as: Coefficients, standard error, t-statistic, P- value, lower 95 percent, and upper 95 percent. Coefficients Standard Error t-Statistic P-Value Lower 95% Upper 95% Intercept 0.739 2.498 0.296 0.768 −4.208 5.686 ??2 0.103 0.008 12.958 1.7E-24 0.088 0.119 Table Summary: Table divided into seven columns summarizes C regressed on X squared. Column 1 notes intercept and X squared. The column headers from 2 to 7 are marked as: Coefficients, standard error, t-statistic, P-value, lower 95 percent, and upper 95 percent. a. Write out the equation for cost per customer as a function of website analysis. Is ??2 statistically significant? Explain. b. Write out the equation for revenue per customer as a function of website analysis. Are ?? and ??2 statistically significant? Explain. c. Assuming the firm’s number of customers is independent of ??, these results imply the marginal revenue, or marginal benefit, of website analysis is ????(??) = 11.09 − 0.2?? and the marginal cost of website analysis is ????(??) = 0.21??. Under this assumption, what level of website analysis will maximize net benefits? 2. Download the Excel file “Data_for_Assignment_2.xls” Watch “Estimating OLS regressions using Excel” at https://www.youtube.com/watch?v=bI6d-Zynt5Y. You may need to setup the “Data Analysis” add-in. The Excel file contains data on ticket prices and their corresponding quantity demanded. a. Plot the demand curve using quantities demanded on column B and prices on comlumn C. Put quantity on the X axis and price on the Y axis. b. What are the averages of prices and quantities? c. Estimate the linear function in the form of ?? = ?? + ???? + ?? Use “Data Analysis”  “Regression”  choose the option “New Woeksheet Ply” and selection “Residuals”, “Residual Plots”, and “Line Fit Plots” Coefficients Standard Error t-Statistic P-Value Lower 95% Upper 95% Intercept ?? https://www.youtube.com/watch?v=bI6d-Zynt5Y i. Write down the estimated equation. What are the estimated ??� and ??�? ii. What are the standard errors and t-statistics for ??� and ??�? Conclude whether they are different from zero. iii. What are the 95% confidence intervals for ??� and ??�? iv. What are the ??2 and adjusted ??2? v. What is quantity demanded at price ?? = 17.67? vi. What is elasticity of demand at price ?? = 17.67? d. Plot the demand curve using log(quantity demanded) on column D and log(price) on comlumn E. Put log(price) on the X axis and log(quantity demanded) on the Y axis. e. Estimate the log-linear regression in the form of ???? ?? = ?? + ?? ???? ?? + ?? i. Write down the estimated equation. What are the estimated ??� and ??�? ii. What are the standard errors and t-statistics for ??� and ??�? Conclude whether they are different from zero. Coefficients Standard Error t-Statistic P-Value Lower 95% Upper 95% Intercept ln?? iii. What are the 95% confidence intervals for ??� and ??�? iv. What are the ??2 and adjusted ??2? v. What is elasticity of demand at price ?? = 17.67?

dataforassignment2-srntli3e.xlsx mbae6865fall2021groupassignment2problems-u0x5htlr.pdf

Suraj · Accepted Answer

Solution 2:
The plot between quantities and price is given as follows:
b)
The average is calculated using Excel. The output table is given as follows:
Thus, the average ticket price is 17.7 and average quantity is 101.8.
c)
The linear regression output is given as follows:
i).
The estimated regression equation is given as follows:
Q = 193.19 - 5.17 * Price
The coefficient of  are given as follows:
ii).
From the above output table, the standard error for intercept term is 4.67 and the test-statistic is 41.36. As the p-value is 0 which is less than 0.05. Hence, the coefficient of a is different from 0.
The standard error of b is 0.25 and the test-statistic value is -20.30. As the p-value is 0 which is less than 0.05. Hence, the coefficient of a is different from 0.
iii).
The 95% confidence interval for both intercept and slope coefficients is taken from the above output table as follows:
The 95% confidence for  is .
The 95% confidence interval for  is .
iv).
The R square and Adjusted R square is taken from the following table:
Thus, the R square value is 0.8079 and Adjusted R square value is 0.8059.
v).
The quantity demanded at Price P =17.67 is calculated using the regression equation:
Q = 193.19 -5.17 * Price
    = 193.19 – 5.17 * 17.67
     = 101.84
vi).
Elasticity of the demand is calculated by taking ratio of demand at price.
Elasticity =
d)
The new plot of log transformation is given as follows:
e)
The linear regression output table is given as follows:
The estimated regression equation is given as follows:
ln(Q) = 7.18 – 0.92 * ln (Price)
The coefficient of  are given as follows:
ii).
From the above output table, the standard error for intercept term is 0.14 and the test-statistic is 50.90. As the p-value is 0 which is less than 0.05. Hence, the coefficient of a is different from 0.
The standard error of b is 0.05 and the test-statistic value is -18.49. As the p-value is 0 which is less than 0.05. Hence, the coefficient of a is different from 0.
iii).
The 95% confidence interval for both intercept and slope coefficients is taken from the above output table as follows:
The 95% confidence for  is .
The 95% confidence interval for  is .
iv).
The R square and Adjusted R square is taken from the following table:
Thus, the R square value is 0.7772 and Adjusted R square value is 0.7749.

Data ObservationActual data Transformed data Number of Tickets SoldTicket PriceNumber of Tickets SoldTicket Price 184254.433.22 2105.9164.662.77 3135.3144.912.64 4107.3184.682.89...

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