Tucson Machinery, Incorporated, manufactures numerically controlled machines, which sell for an average price of $17.0 million each.Sales for these NCMS for the past two years were as follows: Use Exhibit 3.10.QUARTERLAST YEAR134QUANTITY QUARTER(UNITS) THIS YEAR17.233121Y =a. Find the equation of a simple linear regression line using Excel.Note: Round your answers to 3 decimal places.Last Year20.536 +This Yearb. Compute trend and seasonal factor from a linear regression line obtained with Excel.Note: Do not round intermediate calculations. Round your answers to 3 decimal places.Period1234112342QUANTITY(UNITS)16293320340.714 tTrend Forecast0.8001.0471.3670.8980.6641.1681.2920.762SeasonalFactors0.7321.1081.3300.8300.7321.1081.3300.830

Given,QuarterLast YearQuantity(Units)Quarter(This Year)Quantity(Units)117116223229331333421420

Tucson Machinery, Incorporated, manufactures numerically controlled machines, which sell for an average price of $17.0 million each. Sales for these NCMs for the past two years were as follows: Use Exhibit 3.10. QUARTER LAST YEAR QUANTITY (UNITS) 17 23 31 21 QUARTER THIS YEAR 20.536 1 2 QUANTITY (UNITS) 16 29 33 20 a. Find the equation of a simple linear regression line using Excel. Note: Round your answers to 3 decimal places. 0.7141 b. Compute trend and seasonal factor from a linear regression line obtained with Excel. Note: Do not round intermediate calculations. Round your answers to 3 decimal places.

Tucson Machinery, Incorporated, manufactures numerically controlled machines, which sell for an average price of $17.0 million each. Sales for these NCMs for the past two years were as follows: Use Exhibit 3.10. QUARTER LAST YEAR QUANTITY (UNITS) 17 23 31 21 QUARTER THIS YEAR 20.536 1 2 QUANTITY (UNITS) 16 29 33 20 a. Find the equation of a simple linear regression line using Excel. Note: Round your answers to 3 decimal places. 0.7141 b. Compute trend and seasonal factor from a linear regression line obtained with Excel. Note: Do not round intermediate calculations. Round your answers to 3 decimal places.

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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The Wall Street Journal’s website, www.wsj.com, reported the number of cars and light-duty trucks sold through October of 2014 and October of 2015. The top sixteen manufacturers are listed here. The sales information for all manufacturers can be accessed in a data file below. Sales data are often reported in this way to compare current sales to last year’s sales. Year-to-Date Sales Manufacturer Through October 2015 Through October 2014 General Motors Corp. 2,562,840 2,434,707 Ford Motor Company 2,178,587 2,065,612 Toyota Motor Sales USA Inc. 2,071,446 1,975,368 Chrysler 1,814,268 1,687,313 American Honda Motor Co Inc. 1,320,217 1,281,777 Nissan North America Inc. 1,238,535 1,166,389 Hyundai Motor America 638,195 607,539 Kia Motors America Inc. 526,024 489,711 Subaru of America Inc. 480,331 418,497 Volkswagen of America Inc. 294,602 301,187 Mercedes-Benz 301,915 281,728 BMW of North America Inc.…
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An analyst working for your firm provided an estimated log-linear demand function based on the natural logarithm of the quantity sold, price, and the average income of consumers. Results are summarized in the following table: SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept LN Price LN Income df 0.968 0.937 0.933 0.003 30 SS MS F 2 0.003637484 0.001818742 202.48598 0.000242516 8.98206E-06 27 29 0.00388 Coefficients Standard Error 0.57 0.00 0.13 0.51 -0.08 0.15 t Stat 0.90 -19.50 1.13 P-value 0.37 0.00 0.27 Significance F 5.55598E-17 Lower 95% -0.65 -0.09 -0.12 How would a 4 percent increase in income impact the demand for your product? Demand would increase by 60 percent. Demand would increase by 0.6 percent. Demand would decrease by 60 percent. Demand would decrease by 0.6 percent. Upper 95% 1.68 -0.07 0.41
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