Engineering Economy (17th Edition)
Engineering Economy (17th Edition)
17th Edition
ISBN: 9780134870069
Author: William G. Sullivan, Elin M. Wicks, C. Patrick Koelling
Publisher: PEARSON
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Chapter 3, Problem 20P

A company that manufactures shuttle cars and mines for the coal mining industry has determined that “coal production in the U.S.” is a fairly reliable three-quarter leading indicator of their sales. This quarter’s coal production in the United States can be obtained from the Department of Energy and it is used to obtain a forecast of their shuttle car and miner sales nine months from now. For the data below, determine a linear equation based on regression analysis and prepare a forecast of company sales three quarters from now. (3.4 .3)

Chapter 3, Problem 20P, A company that manufactures shuttle cars and mines for the coal mining industry has determined that

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All questions utilize the multivariate demand function for Smooth Sailing sailboats in C6 on text page 83.  Compute to three decimal places. Initial values are:      PX = $9500     PY = $10000   I = $15000      A = $170000   W = 160 This function is:        Qs = 89830 -40PS +20PX +15PY +2I +.001A +10W 1.(a). Use the above to calculate the arc price elasticity of demand between PS = $9000 decreasing to PS = $8000.  The arc elasticity formula is: 1.(b). Judging from the computation in (a), do you expect the revenue resulting from the decrease in Ps to $8000 to increase, remain the same, or decrease relative to the revenue at Ps = $9000. (Hint: see the table on page 65 of Truett).  Explain your choice. 1.(c). Calculate the point elasticity of demand for Smooth Sailing sailboats at PS = $9000 (which should make Qs = 101600).  The formula is: 1.(d). Does this elasticity value indicate that Smooth Sailing demand is relatively responsive to changes in the price of these sailboats?  Explain…
A forecaster used the regression equation Qt= a + bt+q₁D₁ + C2D2 + c3D3 and quarterly sales data for 2004/-2021/V (t = 1, ..., 64) for an appliance manufacturer to obtain the results shown below. Q is quarterly sales, and D1, D₂ and D3 are dummy variables for quarters I, II, and III. DEPENDENT VARIABLE: QT R-SQUARE OBSERVATIONS: 64 0.8768 VARIABLE INTERCEPT T D1 D2 D3 F-RATIO P-VALUE ON F 107.982 0.0001 PARAMETER STANDARD ESTIMATE 30.0 1.5 10.0 25.0 40.0 ERROR T-RATIO P-VALUE 2.34 0.0224 2.14 0.0362 3.33 0.0015 3.47 0.0010 2.53 0.0140 12.80 0.70 3.00 7.20 15.80 In any given year, quarterly sales tend to vary as follows:
Regression analysis was applied between $ sales (y) and $ advertising (r) across all the branches of a major international corporation. The following regression function was obtained. ŷ = 5000 + 7.25r (a) Predict the amount for sales where the advertising amount is $ 1,000,000.00. (b) If the advertising budgets of two branches of the corporation differ by $30,000, then what will be the predicted difference in their sales?
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