ECMB12H3F L30 Quantitative Methods in Economics II Final Examination Wednesday December 14‚ 2011 2–4 pm Instructor: Victor Yu Last Name (Print): Solution First Name (Print): Student Number: Circle your section Aids allowed: L30 Wednesday Deferred Exam Calculator and two aid sheets (four 8.5"x11" pages) written or typed on both sides Time allowed: Two (2) hours This exam consists of 22 questions in 15 pages including this cover page. It is the student’s responsibility to hand in a complete exam
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21‚ 27 and 34 Session 8 Goodness of Fit and Independence Chap. 11 Session 9 Problems Chap. 11: 3‚ 11‚ 13‚ 19‚ and 21 Session 9 Simple Linear Regression Chap. 12 Session 10 Problems Chap. 12: 4‚ 15‚ 18‚ 23‚ 26‚ 32‚ 40 and 47 Session 10 Multiple Regression Chap. 13 Session 11 Problems Chap. 13: 5‚ 15‚ 23‚ 28‚ 32 and 34 Session 11 Regression Analysis: Model Building Chap. 16(annex) Session 12 Problems Chap 16: 1‚ 12‚ 16 and 21 Session 12 Final Exam Every week one team will solve
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Introduction to Linear Regression and Correlation Analysis Goals After this‚ you should be able to: • • • • • Calculate and interpret the simple correlation between two variables Determine whether the correlation is significant Calculate and interpret the simple linear regression equation for a set of data Understand the assumptions behind regression analysis Determine whether a regression model is significant Goals (continued) After this‚ you should be able to: • Calculate and
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CGA-CANADA PERSONAL & CORPORATE TAXATION [TX1] EXAMINATION March 2012 Time: 3 Hours Notes: 1. 2. 3. This examination is based on the Canadian Income Tax Act with Regulations (CCH 92nd Edition). Round all calculations to the nearest dollar‚ except price per share. The following items‚ applicable to the 2011 taxation year‚ are provided for reference: Federal Income Tax Rates — 2011 2011 Taxable Income Up to $41‚544 $41‚545 – $83‚088 $83‚089 – $128‚800 $128‚801 and over Personal Tax Credits 1. 2.
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The start of an exponential smoothing process with an alpha of 0.2 is as follows: Period Actual Forecast 1 1020 2 940 1020 3 920 1004 4 950 What will be the forecast for period 4? A. B. C. D. 1020.8 966.8 875.4 987.2 6. A life insurance salesman sells on average 2.5 life insurances policies per week. What is the probability that he will sell some policies in a given week? A. B. C. D. 0.9179 0.7627 0.9750 0.0821 P.T.O. LUBS5000M 7. Assuming that the salesman in question 6 works a five day
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LINEAR REGRESSION MODELS W4315 HOMEWORK 2 ANSWERS February 15‚ 2010 Instructor: Frank Wood 1. (20 points) In the file ”problem1.txt”(accessible on professor’s website)‚ there are 500 pairs of data‚ where the first column is X and the second column is Y. The regression model is Y = β0 + β1 X + a. Draw 20 pairs of data randomly from this population of size 500. Use MATLAB to run a regression model specified as above and keep record of the estimations of both β0 and β1 . Do this 200 times. Thus you
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Mark Scheme (Results) June 2011 International GCSE Information Communication Technology Paper 01 Edexcel is one of the leading examining and awarding bodies in the UK and throughout the world. We provide a wide range of qualifications including academic‚ vocational‚ occupational and specific programmes for employers. Through a network of UK and overseas offices‚ Edexcel’s centres receive the support they need to help them deliver their education and training programmes to learners
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Chapter 4 Simple regression model Practice problems Use Chapter 4 Powerpoint question 4.1 to answer the following questions: 1. Report the Eveiw output for regression model . Please write down your fitted regression model. 2. Are the sign for consistent with your expectation‚ explain? 3. Hypothesize the sign of the coefficient and test your hypothesis at 5% significance level using t-table. 4. What percentage of variation in 30 year fixed mortgage rate is explained
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appropriate sampling populations and instruments. Other topics include descriptive statistics‚ probability concepts‚ confidence intervals‚ sampling designs‚ data collection‚ and data analysis—including parametric and nonparametric tests of hypothesis and regression analysis. Policies Faculty and students will be held responsible for understanding and adhering to all policies contained within the following two documents: • University policies: You must be logged into the student website to view this
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Multi Regression Problem for Wine Quality The purpose of this regression analysis was to test wine quality. An evaluation like this would help assure quality for the wine market. We collected or data from “Machine Learning Repository” a data mining website. The data we obtained from Machine Learning Repository compares variables such as fixed acidity‚ volatile acidity‚ citric acid‚ residual sugar‚ chlorides‚ free sulfur dioxide‚ total sulfur dioxide‚ density‚ pH‚ sulphate‚ and alcohol to help
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