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How to Analyze the Regression Analysis Output from Excel In a simple regression model‚ we are trying to determine if a variable Y is linearly dependent on variable X. That is‚ whenever X changes‚ Y also changes linearly. A linear relationship is a straight line relationship. In the form of an equation‚ this relationship can be expressed as Y = α + βX + e In this equation‚ Y is the dependent variable‚ and X is the independent variable. α is the intercept of the regression line‚ and β is the
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CHAPTER 16 SIMPLE LINEAR REGRESSION AND CORRELATION SECTIONS 1 - 2 MULTIPLE CHOICE QUESTIONS In the following multiple-choice questions‚ please circle the correct answer. 1. The regression line [pic] = 3 + 2x has been fitted to the data points (4‚ 8)‚ (2‚ 5)‚ and (1‚ 2). The sum of the squared residuals will be: a. 7 b. 15 c. 8 d. 22 ANSWER: d 2. If an estimated regression line has a y-intercept of 10 and a slope of 4‚ then when x = 2 the actual value
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ANALYSIS OF SICKNESS ABSENCE USING POISSON REGRESSION MODELS David A. Botwe‚ M.Sc. Biostatistics‚ Department of Medical Statistics‚ University of Ibadan Email: davebotwe@yahoo.com ABSTRACT Background: There is the need to develop a statistical model to describe the pattern of sickness absenteeism and also to predict the trend over a period of time. Objective: To develop a statistical model that adequately describes the pattern of sickness absenteeism among workers. Setting: University College
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Regression with Discrete Dependent Variable CE 601 Term Project By Classification Type of Discrete Dependent Variable Example Problems Type of Regression Model Binary 1. Consumer economics 2. Decision to vote Logistic Regression Probit Regression Ordinal 1. Opinion survey 2. Rating systems Ordered Logistic Regression Ordered Probit Regression Nominal 1. Occupation choice 2. Blood type Multinomial Logistic Regression Count 1. Consumer demand 2
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research provides statistical analysis for gross monthly sales in 60 stores using five key measures within a 10km vicinity: number of competitors‚ population in ‘000’s‚ average population income‚ average number of cars owned by households‚ and median age of dwellings. These quantitative variables are the key determinants‚ which will provide substance for descriptive statistics and the multiple linear regression model. This research reports mainly on statistical analysis‚ providing a direct interpretation
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Solutions Manual Econometric Analysis Fifth Edition William H. Greene New York University Prentice Hall‚ Upper Saddle River‚ New Jersey 07458 Contents and Notation Chapter 1 Introduction 1 Chapter 2 The Classical Multiple Linear Regression Model 2 Chapter 3 Least Squares 3 Chapter 4 Finite-Sample Properties of the Least Squares Estimator 7 Chapter 5 Large-Sample Properties of the Least Squares and Instrumental Variables Estimators 14 Chapter 6 Inference and Prediction 19 Chapter 7
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decisions with fewer errors. In this paper‚ demand estimation will be done through a regression analysis. This analysis will examine the elements that management should look at when determining demand for a product such as: price‚ competitor’s price‚ customer income‚ advertising and the cost of microwave ovens. The main objective of this paper will be to: estimate the demand function using regression analysis‚ find elasticities of demand with respect to various variables and make forecasting decisions
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Correlation and Regression Assignment Problem 1. a. Explain which variable you chose as the explanatory variable and discuss why. * The explanatory variable is the height. This is because I am assuming that as height increases‚ the weight will increase as well. So the weight is the dependent variable b. Produce a scatter plot and insert the result here. * Scatter plot c. Find the equation of the regression line‚ Write it in the form of y=a+bx‚ where a is the y-intercept
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Comparative Analysis Case The Coca-Cola Company and PepsiCo‚ Inc. Both Coca-Cola Company and PepsiCo‚ Inc. used a comparative report format‚ that list the sections one above the other‚ on the same page‚ to present their balance sheets. For a measure of both a company’s efficiency and its short-term financial health‚ the working capital is calculated as: Working Capital = Current Assets – Current Liabilities. At the end of 2007‚ the Coca-Cola Company has a negative working capital of $1‚120
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