Joan Holtz CASE 5-3 JOAN HOLTZ (A)* (1) Electric utility bills. An electric utility company can estimate with reasonable certainty the expected revenue in a given period by taking into consideration some of the following: customer habits‚ average historical trends‚ demand and supply forecasts‚ and environmental changes. The electric utility industry effectively uses an insurance industry concept—the law of large numbers‚ to determine with certainty‚ expected revenue. The law of large numbers
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To estimate impedance function‚ distance as a proxy of travel cost between pairs of origins and destinations is calculated by ARC GIS 10.2 which considers the length of the shortest available route. To calibrate the best impedance function‚ the frequency distribution of walking trips is plotted against distance. By fitting different types of functions (i.e.‚ exponential‚ multiplicative exponential‚ linear‚ logarithmic‚ polynomial‚ power) and comparing standard error of the estimates’ values‚ the
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If the expectancy of the attributes or criteria is larger the better; = (2) If the expectancy of the attributes or criteria is smaller the better; = (3) where; and are the maximum and minimum value of each alternative respectively. Normalized decision matrix is as follows; = (4) (4) Calculate preference variation value for all criteria as per following equations; = ] (5) where; = (6) (5) Calculate deviation in preference value for all criteria
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#include "stdafx.h" #include "windows.h" #include "glut.h" #include "gl/GL.h" #include "gl/Glu.h" GLfloat spe_x = 1.0f; GLfloat spe_y = 1.0f; GLfloat spe_z = 1.0f; GLfloat spe_a = 1.0f; GLfloat wall_1 = 1.0f; GLfloat translate_x = 0.6f; GLfloat translate_y = 0.38f; GLfloat translate_z = 0.5f; float jack_radius = 0.1; bool isTrue = false; bool isTrue_r = false; GLfloat rot = 90.0; // Wall void wall(double thickness) { // draw thin wall with top xz-plane‚ corner at origin glPushMatrix();
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Markov’s Trilemma First we try to find the optimal portfolio for our original set up. Weighting Asset GM -0.8% MRK 34.8% GE 66.0% 100.0% Risk-free rate 7% Expected Return 41.3% Expected standard deviation 21.4% Sharpe Ratio 1.60 1. Then we try the following actions and try to understand their consequences: a. Suppose that GM has decided to become a diversified conglomerate‚ much like GE‚ so that its correlation with GE will be 0.80 instead of 0.26. Weighting
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CLICK TO DOWNLOAD MAT 540 Midterm Exam 1. Deterministic techniques assume that no uncertainty exists in model parameters. 2. A continuous random variable may assume only integer values within a given interval. 3. An inspector correctly identifies defective products 90% of the time. For the next 10 products‚ the probability that he makes fewer than 2 incorrect inspections is 0.736. 4. A decision tree is a diagram consisting of circles decision nodes‚ square probability nodes‚ and
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LEAD 6341 Research Methods and Statistics Midterm Exam Part II: Conceptual Problems (Open Book) Spring‚ 2013 1) Very briefly discuss the history of ethical problems in research in the US. Describe how current research policies and practices reduce the likelihood of ethical problems arising from research today. The Tuskegee study is an example of ethical problem in research in the US. The black subjects were promised medical care‚ meals‚ and burial insurance for their participation in
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SIG Interview Questions 1. Torpedo question: 2 torpedoes‚ each with 1/3 probability of hitting/ sinking a ship 2. I have 20% chance to have cavity gene. If I do have the gene‚ there is 51% chance that I will have at least one cavity over 1 year. If I don’t have the gene‚ there is 19% chance that I will have at least one cavity over 1 year. Given that I have a cavity in 6 months‚ what’s the probability that I have at least a cavity over 1 year? 3. What is the probability of 5 people with different
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Examining Stock Returns for Normal Distributions July11‚ 2012 Part A. A1 (CRSP 2000-2008) | VW Daily | EW Daily | VW Monthly | EW Monthly | Mean | 0.00% | 0.05% | -0.12% | 0.50% | σ | 1.35% | 1.12% | 4.66% | 6.14% | Table A1 shows return means and standard deviations for the CRSP market portfolio from 2000-2008. In comparing daily vs monthly returns in both cases‚ equally weighted (EW) and value weighted (VW)‚ Table A1 shows the mean and standard deviation are
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1.if selecting samples of size n = 10 from a population with a known mean and standard deviation what requirement‚ if any must be satisfied in order to assume that the distribution of the sample means is a normal distribution The population must have a normal distribution. 2. find the area of the shaded region. The graph depicts that standard normal distribution with mean 0 and standard deviation 1. M: 0 δ: 1 Z: 1.13= .8708 2ND DIST. #2 LOWER: -999999 UPPER: 1.13 U: 0 δ: 1 =.8707618393 3. Shaded
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