0.0749 + 0.0749 = 0.1498. 2. [§8-53] Let X1 ‚ . . . ‚ Xn be i.i.d. uniform on [0‚ θ]. (a) Find the method of moments estimate of θ‚ and the mean‚ variance‚ bias‚ and MSE of the MME. (b) The mle of θ is θˆ = max Xi . The pdf of max1≤i≤n Xi (How do we 1≤i≤n find this? ) is n−1 nx f (x|θ) = θn 0 0<x<θ . otherwise Calculate the mean and variance of the mle.
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could carry out calculations easily. Methodology First‚ since all the data came from the case and was already on an Excel spreadsheet‚ we began by calculating the expected time‚ variance‚ expedition available and slope for each task using the formulas below. Expected time=(optimistic+4*(most likely)+pessimistic)/6 Variance=((pessimistic-optimistic)/6)^2 Expedition available=Crash time-Expected time Slope= Expedition available/(Crash cost-Normal cost) Calculation results can be found in Table 1 in
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Using EXCEL for Asset Allocation and Performing Market Efficiency Studies 1. Introduction There are several features in EXCEL that are very useful for asset allocation and performing market efficiency studies. These features used in conjunction with live or historical data allows one to apply the sophisticated techniques discussed in this class in practical situations. This write-up will introduce students to the various mathematical and statistical functions available in EXCEL and explain
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University of Phoenix OnlineCourse: RES / 341QUIZ # 1(Chapter 3 and 4 from Applied Statistics in Business and Economics )45 Questions [Each Question = 1 Point]SOLUTIONPlease mark one answer for all multiple choice questions with RED!Chapter 3Multiple Choice1. Which is not a tip for effective bar charts?A) Time usually goes on the horizontal axis. B) Bar height or length should be proportional to the quantity displayed. C) Label data values at the top of each bar unless graphing lots of data. D)
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| Basic math symbols Symbol | Symbol Name | Meaning / definition | Example | = | equals sign | equality | 5 = 2+3 | ≠ | not equal sign | inequality | 5 ≠ 4 | > | strict inequality | greater than | 5 > 4 | < | strict inequality | less than | 4 < 5 | ≥ | inequality | greater than or equal to | 5 ≥ 4 | ≤ | inequality | less than or equal to | 4 ≤ 5 | ( ) | parentheses | calculate expression inside first | 2 × (3+5) = 16 | [ ] | brackets | calculate expression inside first
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well. How can I help you? Well Caroline‚ I wanted to discuss with you the results of your Dept 1880 Retail Marketing‚ budget variance vs. actual for Jun 2011. Sure‚ Let me get my notes out that I had submitted to your group. I emailed you a copy as well with your comments for this review. Did you receive it? Yes‚ I did Ok‚ there were 3 main categories where the variance between actual and budget were the highest. Those categories are Compensation‚ Marketing‚ IT‚ and then we put everything else
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Running Heading: COST ALLOCATION AND VARIANCES Cost Allocation and Variances- Chapter 12 & 13 Text Book Questions Stacey S. Swafford University of Phoenix ACC 561 Dr. Janice Mereba April 23‚ 2010 Chapter 12 Excel Application Exercise 12-59: Allocating Costs Using Direct and Step-Down Methods p. 584 Goal: Create an Excel spreadsheet to allocate costs using the direct method and the step-down method. Use the results to answer questions about your findings. Scenario: Antonio
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1 Factor Models The Markowitz mean-variance framework requires having access to many parameters: If there are n risky assets‚ with rates of return ri ‚ i = 1‚ 2‚ . . . ‚ n‚ then we must know 2 all the n means (ri )‚ n variances (σi ) and n(n − 1)/2 covariances (σij ) for a total of 2n + n(n − 1)/2 parameters. If for example n = 100 we would need 4750 parameters‚ and if n = 1000 we would need 501‚ 500 parameters! At best we could try to estimate these‚ but how? In fact‚ it is easy to see
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TORONTO Joseph L. Rotman School of Management RSM332 PROBLEM SET #2 SOLUTIONS 1. (a) Expected returns are: E[RA ] = 0.3 × 0.07 + 0.4 × 0.06 + 0.3 × (−0.08) = 0.021 = 2.1%‚ E[RB ] = 0.3 × 0.14 + 0.4 × (−0.04) + 0.3 × 0.08 = 0.05 = 5%. Variances are: 2 σA = 0.3 × (0.07)2 + 0.4 × (0.06)2 + 0.3 × (0.08)2 − (0.021)2 = 0.004389‚ 2 σB = 0.3 × (0.14)2 + 0.4 × (0.04)2 + 0.3 × (0.08)2 − (0.05)2 = 0.00594. Standard deviations are: √ 0.004389 = 6.625%‚ σA = √ 0.00594 = 7.707%. σB = Covariance
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ECON10005 QUANTITATIVE METHODS 1 Assignment 2 Semester 1‚ 2013 This assignment has four questions‚ and is due by 5.00pm on Thursday 2 May. It is to be submitted electronically as a .pdf file using the assignment tool on the subject’s LMS page. Marks depend on your tutor being able to understand your statements and arguments‚ so marks may be deducted for poor presentation or unclear language. Use nothing smaller than 12 point font. If you wish to write your assignment by hand and scan the file into
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