9. Suppose we modify the production model in Section 1.3 to obtain the following mathe-matical model:Max 10xS.t.ax < 40x 2 0where a is the number of hours of production time required for each unit produced. Witha = 5, the optimal solution is x = 8. If we have a stochastic model with a = 3, a = 4, a = 5,or a = 6 as the possible values for the number of hours required per unit, what is the optimalvalue for x? What problems does this stochastic model cause?

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Answered: Suppose we modify the production model…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Use the data below to solve for the following: 2. Naïve method 3. Unweighted 3 month moving average 4. Weighted Moving Average (3 months, with the following weights: 0.45, 0.35, 0.20) 5. Simple Exponential Smoothing with the following parameters: Ft+1=32 and the α = .15 6. Time Series Regression Months 1 2 3 4 5 6 7 8 9 10 11 12 Firm's Actual Market share 30 32 33 34 28 33 29 27 32 33 28 33 7. Which of the following forecasting method will you use? 8. What are your basis in choosing for your forecasting techniques? Explain briefly. ONLY DO 56
(c) Compute EVPI and EVSI (in thousands of dollars). (Round your answers to one decimal place.) EVPI $ 3.6 EVSI $ 3.6 Xthousand x thousand Discuss whether the firm should consider a consulting expert who could provide independent forecasts of market conditions for the product. Compared to the EVPI, the EVSI has a low value. This indicates additional information is probably worthwhile
Cascade Pharmaceuticals Company developed the following regression model, using time-series data from the past 33 quarters, for one of its nonprescription cold remedies: Y = -1.04 +0.24X₁-0.27X2 where Y = quarterly sales (in thousands of cases) of the cold remedy X₁ = Cascade's quarterly advertising (x $1,000) for the cold remedy X₂ = competitors' advertising for similar products (x $10,000) Here is additional information concerning the regression model: Sb1 = 0.052, Sb2 = 0.070, R² = 0.640, se = 1.63, F-statistic = 31.402, and Durbin-Watson (d) statistic = 0.499. Which of the independent variables (if any) appears to be statistically significant (at the 0.05 level) in explaining sales of the cold remedy? (Hint: to.05/2,33-3= 2.042.) Check all that apply. O X₁ O X₂ What proportion of the total variation in sales is explained by the regression equation? O 0.122 O 0.070 O 0.640 O 0.052 The given F-value shows that you reject the null hypothesis that neither of the independent variables…
5. You invest to maximize utility: U = a, -A o. You have an information ratio of 0.5, and a risk aversion parameter, 2, of 12 (in decimal units per year). So, for example, an alpha of 3%, and a risk of 5%, would lead to utility of zero.
c) When an exponential smoothing model is used with a smoothing parameter alpha of 0.80 and an April forecast is 150, what is the forecast on the sales in May. (Hint: F#1=aYt+(1-a)Ft), For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac). BIUS Arial 10pt A V ... Paragraph v2 X, ABC EX 3B HE !!! C !!!
Can you do this using uhligs method please
Question 3 (a) Consider a model of market equilibrium in which the current supply of firms is a function of the price that is expected to prevail when the product is sold. Assume that the market supply equation is q³(t) = F + Gp and pe is the expected price and F and G are constant parameters of the supply equation. Assume further that suppliers use information about the actual current price and its first and second derivatives with respect to time to form their prediction of the price that will prevail when their product reaches the market. In particular, assume that dp pe=p+b+c- dt d²p dt² tdpd²p=0, then suppliers and b> c> 0. If the current price is constant, so that dt expect the prevailing price to equal the current price. If the current price is rising, so that > 0, then suppliers expect the prevailing price to be higher than the current dt price. How much higher depends on whether the current price is rising at an increasing rate, > 0; or at a decreasing rate, p 0 is a constant…
State at least one conclusion from your data/graph (For example: State X has lost population by 10000 people, Region X is grew 10% over the last 50 years, etc.)
Consider a regression model Yi=B1+B2xi+ui and you estimated B2hat =0.3. This implies that a unit charge x is predicted to a) increase the probability of Y=1 by 30 percentage points b) increase the probability of Y=1 by 30 percent c) increase Y by 0.3 units d) increase Y by 30%
1

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