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    INFERENTIAL STATISTIC

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    data for the independent variables for Melks. Descriptive statistics   Income Age Count 300 300 Mean 56‚426.45 45.91 sample standard deviation 3‚876.30 7.23 sample variance 15‚025‚706.87 52.29 Minimum 50000 34 Maximum 60000 55 Range 10000 21 confidence interval 95.% lower 54‚135.75 41.64 confidence interval 95.% upper 58‚717.16 50.18

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    Stroop Effect

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    Exploring the Stroop Effect by using numbers Abstract The purpose of this experiment is to study automatic processes by replicating the previously carried out Stroop effect by using numbers. This experiment was conducted by recruiting 8 participants (4 males and 4 females)‚ who are working in a head-office of Save the Children Organization in Yangon‚ selected by an opportunistic sample. Participants were presented with a Stroop-experiment-task sheet which consists of two parts which was the congruent

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    STA9708 Regression Analysis: Literacy rates and Poverty rates As we are aware‚ poverty rate serve as an indicator for a number of causes in the world. Poverty rates are linked with infant mortality‚ education‚ child labor and crime etc. In this project‚ I will apply the regression analysis learned in the Statistics course to study the relationship between literacy rates and poverty rates among different states in USA. In my study‚ the poverty rates will be the independent variable (x) and literacy

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    Stat 225

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    1 of 11 ID: MST.CPD.UD.03.0010 William is a quality inspector for an appliance manufacturer and is currently testing an oven. The oven starts off at room temperature‚ which is 70 degrees Celsius. William turns the oven to 167 degrees. The temperature in the oven increases from 70 degrees to 167 degrees over the following 10 minutes at a constant rate‚ so that the temperature follows a uniform distribution over the interval between 70 degrees and 167 degrees. At a randomly chosen time during that

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    Acct 5210 Problem Set 1

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    FINA 5210 Problem Set 1 (Group 305) Problem 1 (a) WpC=[E(rp)-rf] ÷Aσp2 =6%÷2.5×(20%)2 =60% WfC=100% - 60% = 40% (b) Expected return of Complete portfolio is: rCEc= WpC×E(rp)+ WfC×rf =60%×10% + 40%×4% =7.6% The standard deviation of Complete portfolio is: σc = WpC × σp = 60% × 20% = 12% Certainty-equivalent rate of return for investing in C: rc CE= Uc = rCEc- 1/2Aσc2 = 7.6% - 0.5×2.5×12%2 = 5.8% Certainty-equivalent rate of return for investing in P: rp CE= Up= rCEp- 1/2Aσp2

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    Balance Sheet and Net Income

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    Financial Accounting   1. Obligation of business that represents the claims of these against the assets of the less cash is called? A. Asset B. An expense (WA) C. Revenue D. An equity E. Liability   2. Net income results when A. Assets > liability B. Revenue = expenses C. Revenue > expenses D. Revenue < expenses E. None    3. Resources owned by a business are referred to as A. Stockholders equity B. Liability C. Assets D. Revenue (WA) E. None      4. Expenses are incurred

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    Miss.Independent

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    # 0703 Firm Growth: A Survey by Alexander Coad The Papers on Economics and Evolution are edited by the Evolutionary Economics Group‚ MPI Jena. For editorial correspondence‚ please contact: evopapers@econ.mpg.de ISSN 1430-4716 © by the author Max Planck Institute of Economics Evolutionary Economics Group Kahlaische Str. 10 07745 Jena‚ Germany Fax: ++49-3641-686868 #0703 Firm Growth: A Survey∗ Alex Coad a b c† a Max Planck Institute of Economics‚ Jena‚ Germany b Centre

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    definition of the kth origin moment‚ we have: k = (1) Whether X is discrete or continuous‚ 1 = E(X) = ‚ i.e.‚ the 1st origin moment is simply the population mean (i.e.‚ 1 measures central tendency). (2) Since the population variance‚ 2‚ is the weighted average of deviations from the mean squared over all elements of Rx‚ then 2 = E[(X )2] = 2. Therefore‚ the 2nd central moment‚ 2 = 2‚ is a measure of dispersion (or variation‚ or spread) of the population. Further‚ the

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    Beta Management

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    based out of California and was hit very hard by the recent earthquake. The first thing that is necessary to do in this situation is to look into the historic performance of the stocks verse the rest of the market. This is done by calculating the variance of all the stocks‚ and the covariance of the stock to the rest

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    88 0.58 4.43 4.17 6.64 1.20 Median 0.56 16.00 11.50 15.50 12.00 316.80 106.00 205.30 80.50 Mode 0.69 16.00 11.00 16.00 9.00 316.80 76.50 Standard Deviation 0.21 5.38 3.00 4.98 3.28 25.05 23.62 37.56 6.81 Sample Variance 0.04 28.91 9.02 24.78 10.78 627.34 557.72 1410.42 46.39 Kurtosis -1.28 1.02 0.10 1.19 -0.45 1.41 -0.63 0.07 -0.37 Skewness -0.05 0.45 0.61 0.58 0.19 0.83 0.49 -0.39 0.15 Range 0.75 26.00 12.00 24.00 13.00 113.40

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