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    Subject and problems in the Assignment Chap. Due for Session 1 Data and Descriptive Statistics Chap. 1 and 2 Session 2 Problems Chap. 1: 2‚ 3 and 14 Problems Chap. 2: 7‚ 15‚ 29 and 30 Session 2 Descriptive Statistics and intro. to Prob. Chap. 3 and 4 Session 3 Problems Chap. 3: 8‚ 27‚ 29‚ 41‚ 45‚ 53 and 54 Problems Chap. 4: 6‚ 10‚ 15‚ 17‚ 23‚ 28‚ 33 and 42 Session 3 Probability Distributions Chap. 5 and 6 Session 4 Problems Chap. 5: 7‚ 8‚ 18‚ 30‚ 39‚ 42 and 50 Problems Chap.

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    and the number of construction permits issued at present. Example 2: The demand for new house or automobile is very much affected by the interest rates changed by banks. Regression analysis is one such causal method. It is not limited to locating the straight line of best fit. Types:- 1. Simple (or Bivariate) Regression Analysis: Deals with a Single independent variable that determines the value of a dependent variable. Ft+1 = f (x) t Where Ft+1: the forecast for the next period. This

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    Applied Linear Regression Notes set 1 Jamie DeCoster Department of Psychology University of Alabama 348 Gordon Palmer Hall Box 870348 Tuscaloosa‚ AL 35487-0348 Phone: (205) 348-4431 Fax: (205) 348-8648 September 26‚ 2006 Textbook references refer to Cohen‚ Cohen‚ West‚ & Aiken’s (2003) Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. I would like to thank Angie Maitner and Anne-Marie Leistico for comments made on earlier versions of these notes. If you

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    Chapter 6: Multiple Linear Regression Data Mining for Business Intelligence Shmueli‚ Patel & Bruce © Galit Shmueli and Peter Bruce 2010 Topics Explanatory vs. predictive modeling with regression Example: prices of Toyota Corollas Fitting a predictive model Assessing predictive accuracy Selecting a subset of predictors (variable selection) Explanatory Modeling Goal: Explain relationship between predictors (explanatory variables) and target  Familiar use of regression in data analysis 

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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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    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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    Regression Analysis: A Complete Example This section works out an example that includes all the topics we have discussed so far in this chapter. A complete example of regression analysis. PhotoDisc‚ Inc./Getty Images A random sample of eight drivers insured with a company and having similar auto insurance policies was selected. The following table lists their driving experiences (in years) and monthly auto insurance premiums. Driving Experience (years) Monthly Auto Insurance Premium 5 2 12 9

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    Protein Article Search I reviewed “6 Biggest Nutritional Problems Solved” (2008) written by Chris Aceto and Eric Velazquez on the subject of amino acids and how they relate to athletics. The authors believe body builders commonly go overboard in their quest for muscular bodies and neglect key ingredients necessary for muscle production. This relates to amino acids because the authors suggest that athletes frequently leave out fats and proteins made from amino acids. The authors state that

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    Environmental problems‚ ranging from Antarctic Ozone hold to global warming‚ are becoming severe and urgently needed to be tackled with. It has gone beyond national boundaries and become an issue that can be only solved by the cooperation of all the countries in the world.  Firstly‚ the seriousness of the environmental problems has gone beyond the individual country’s ability to solve. The environment has been polluted for hundreds of year by all the people in every county. Due to lacking of capital

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    Toronto Contents Preface 1 Quantitative Methods: Should We Bother? 1.1 Solutions 1.2 Computational supplements 1.2.1 Optimal mix problem Calculus 2.1 Solutions Linear Algebra 3.1 Solutions Descriptive Statistics: On the Way to Elementary Probability 4.1 Solutions Probability Theories 5.1 Solutions 5.2 Additional problems 5.3 Solutions of additional problems Discrete Random Variables 6.1 Solutions vii 1 1 3 3 7 7 15 15 25 25 29 29 30 31 33 33 v 2 3 4 5 6 vi CONTENTS

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