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    Random Sampling

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    Source: Frerichs‚ R.R. Rapid Surveys (unpublished)‚ © 2008. NOT FOR COMMERCIAL DISTRIBUTION 3 Simple Random Sampling 3.1 INTRODUCTION Everyone mentions simple random sampling‚ but few use this method for population-based surveys. Rapid surveys are no exception‚ since they too use a more complex sampling scheme. So why should we be concerned with simple random sampling? The main reason is to learn the theory of sampling. Simple random sampling is the basic selection process of sampling and is

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    Finance Chapter 7 handout

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    0.30 E(R) 8.5% Covariance 0.014177 15.68% 11.91% 0.0153 Corr. 0.0246 9.76% S.D. 10.25% 0.009525 Variance 12% 0.99   EQ 7.2 Expected Return:     E(RA) = (0.3) (‐0.05) + (0.4) (0.10) + (0.3) (0.20) = 0.085 = 8.5%  E(RB) = (0.3) (‐0.10) + (0.4) (0.15) + (0.3) (0.30) = 0.12 = 12%  EQ 7.3 Variance of Return:    Var(RA) = (0.3) (‐0.05 – 0.085)2 + (0.4) (0.10 – 0.085)2 + (0.3)(0.20 – 0.085)2 = 0.009525  SD(RA) = Var(RA) ½ = (0.009525) ½ = 0

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    sample mean and variance of monthly 2 returns of a risky asset. Denote µa and σa the annualized sample mean and variance of returns of the risky asset. Then 2 (a). µa = 0.01 and σa = 0.024; 2 (b). µa = 0.12 and σa = 0.024; 2 (c). µa = 0.12 and σa = 0.288; (d). µa = 0.12 and σa = 0.024; (e). None of the above. 2. Which of the following statements is correct? (a). Expected utility of wealth is constant on the MVS. (b). In the standard deviation and expected return space‚ the mean-variance combination

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    Brown And Warner Event Study

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    generally present few difficulties for event studies. Standard procedures are typically well-specified even when special daily data characteristics are ignored. However‚ recognition of autocorrelation in daily excess returns and changes in their variance conditional on an event can sometimes be advantageous. In addition‚ tests ignoring cross-sectional dependence can be well-specified and have higher power than tests which account for potential dependence. 1. Introduction This paper examines properties

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    master

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    and alternative hypotheses. 4. A random sample is obtained from a population with variance ‚ and the sample mean is computed. Test the null hypothesis versus the alternative hypothesis with . compute the critical value ̅ and state your decision rule for the following options: a) Sample size b) Sample size c) Sample size d) Sample size 5. A random sample of is obtained from a population with variance ‚ and the sample mean is computed. Test the null hypothesis versus the People who

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    Npa, Npa Assets

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    Non Performing Assets (npa) in sbi Getting current updates and regulations for the non performing assets (npa) in sbi With a steep rise in the ratio of the nonperforming assets all over the country‚ it has been really tough for the RBI to control and manage in the given time frame. No doubt‚ public sector banks including SBI have been in the list of banks that have been implementing the procedures to control the default line of the borrowers. On the other hand‚ it should also be noted that nonperforming

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    Week 1 Preparation Notes

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    QUANTITATIVE RESEARCH METHODS WEEK 1 Date: 28 March 2015 Session Time: 14:00 Course Name: Quantitative Research Methods Meeting location: Meeting Room 3 Discussion subject(s): Summary Statistics T-test One-way ANOVA Contents Introduction 3 Introductory information 3 Summary Statistics 3 Basic Definitions 3 T-test 5 Independent samples t test 5 SPSS Steps 5 One-way ANOVA 6 SPSS Steps 6 Introduction This document focuses specifically on Block/Week 1. The following topics will be covered: Introductory

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    case‚ whether TATA STEEL or JSP‚ the annualized return is negative. Q) Construct 10 different portfolios with another company (Correl < 0.70) and compute return and risk for each portfolio. Identify the best portfolio. Construct the minimum variance portfolio. Company | Correl | JSP AND TATA STEEL | 0.89 | JSP AND CUMMINS | 0.65 | Initially we compared JSP and TATA STEEL. We found the Correl = 0.89 which was greater than 0.70. Next we compared JSP and Cummins and found the Correl

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    Discovering Statistics Using SPSS by Mediasamenvattingen2011 The Marketplace to Buy and Sell your Study Material Buy and sell all your summaries‚ notes‚ theses‚ essays‚ papers‚ cases‚ manuals‚ researches‚ and many more.. www.stuvia.com Stuvia.com - The Marketplace to Buy and Sell your Study Material - Field: Discovering Statistics Using SPSS chapter 1‚ 2‚ 3‚ 6‚ 7‚ 8‚ 9‚ 10‚ 11‚ 17‚ 18 Field Chapter 1: Why is my evil lecturer forcing me

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    UDJ | FINANCE | Use/Name | Formula | Use/Name | Formula | Variance (2) (For Poisson‚ equal to mean) | or n*p*(1-p) | NPV (Costs up front) | | Standard Deviation () | | Discount Factor | _1_ (1+r)n | Exp. Val E(W) of combined linear function | a + bμx + cμx Where b&c are weights | Annuity Discount Factor | 1-DF or 1-_1_ k ( 1+r)n k | Variance (2) of combined lin funct (X‚Y) | b2V(x)+c2V(y)+2bc•Cov(x‚y) Where b&c are

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