1/08/13 Probability Primer Principles of Econometrics‚ 4th Edition Probability Primer Page 1 ! Announcement: ! Please make sure you know who your tutor is and remember their names. This will save confusion and embarrassment later. ! Kai Du (David) ! Ngoc Thien Anh Pham (Anh) ! Zara Bomi Shroff Principles of Econometrics‚ 4th Edition Probability Primer Page 2 Chapter Contents ¡ P.1 Random Variables ¡ P.2 Probability Distributions ¡ P.3 Joint
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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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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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purchased to detect any unusual deviations from its benchmarks. Recommendation: Standard costing is a great tool for this company and they must continue to use it. It will aid in helping management analyze actual costs versus standard costs. The variances that can be calculated will help them make future decisions in regard to cost cutting and also many other things such as what quality materials to use in production. Analysis: During May Direct materials per unit = 110‚000 square
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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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these three possibilities‚ I will address the company’s desire to finish the warehouse expansion in 40 weeks. To do this‚ I used the expected time formula‚ the variance formula‚ standard variance and the “z score.” In the formulas below‚ the optimistic outlook is “a”‚ the most likely is “m”‚ and the pessimistic is “b‚” ℴ is standard variance and the z score is used to find the percentage the warehouse is able to be built in 40 weeks. Additionally‚ the actual expected time is 43 weeks‚ shown below is
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$16‚650 Budgeted Profit $606‚350 Hours billed variance =(Actual Hrs billed - Budget Hrs billed)*Budgeted Avg billing rate $278‚100 F Average billing rate variance =(Actual Avg billing rate - Budget Avg billing rate)*Actual Hrs billed ($246‚090) U # of consultants variance =(Budget # of consultants - Actual # of consultants)*Budget avg compensation per consultant ($133‚200) U Compensation rate variance =(Budget Avg compensation per consultant - Actual Avg compensation
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Determine the revenue variance from Arcadia Hospital’s 2005 budget. Is the variance positive or negative? Upon reviewing the Arcadia Hospital Income Statement for the year of 2005‚ I would say that the variance is negative because the actual budget for 2005 $568 million minus the budget of $596 million equals a negative amount of $28 million under budget‚ which means less revenue. In other word‚ revenues were $28 million below budget‚ therefore the variance is negative. Which is desirable
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coefficient estimates. However‚ it typically causes OLS to no longer be the minimum-variance estimator. The error term causes the independent variable to fluctuate more‚ increasing their variance. Moreover‚ the OLS estimates of the standard errors become biased‚ leading to unreliable hypothesis testing. Heteroskedasticity increases the variance of the estimated coefficients variance‚ but OLS underestimates the variance. -impure heteroskedasticity caused by an omitted variable will have possible specification
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