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    constant support and love. Regards‚ RESHAM SHARDA SONA CHAUDHARY SUGANDH KUMARIA SAMRIDHI SHARMA MANISHA NIRALA ABSTRACT This study focuses on the factors affecting the BSE Sensex. Using time series data from the years 1993-94 to 2013-2014 multiple regression analysis is applied to find out significant relationships between the dependent variable BSE Sensex and independent variables including Gold Prices‚ Foreign Exchange Reserves and the Exchange Rate. This study indicates a strong positive relation

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    2) Basic Ideas of Linear Regression: The Two-Variable Model In this chapter we introduced some fundamental ideas of regression analysis. Starting with the key concept of the population regression function (PRF)‚ we developed the concept of linear PRF. This book is primarily concerned with linear PRFs‚ that is‚ regressions that are linear in the parameters regardless of whether or not they are linear in the variables. We then introduced the idea of the stochastic PRF and discussed in detail the nature

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    Class Essay

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    1. Dataset 3 Questions related to Simple Regression 2. Solutions to Dataset 3 (including supporting figures) 3. Dataset 4 Questions related to Multiple Regression 4. Solutions to Dataset 4 (including supporting figures) University of Queensland | ECON 7300‚ STATISTICS FOR BUSINESS AND ECONOMICS‚ 2 STATISTICAL PROJECT October 14‚ 2013 [SANDEEP MAHAPATRA‚ 42982160 & WENQIAN ZHANG‚ 43260865 ] Instructions for Dataset 3: SIMPLE REGRESSION ANALYSIS (30 Marks) A statistician collected

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    paper

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    LECTURE 10 4TH STAGE OF QUANTITATIVE ANALYSIS: ANALYZING DATA Simple Regression to Multiple Regression Analysis: Introductory Material (Estimating and Evaluating the Estimated Model) PART – I: Simple/two-variable regression analysis Simple regression analysis: an example Assuming a survey of 10 families yields the following data on their consumption expenditure (Y) and income (X). Y (Thousands) X (Thousands) 70 80

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    Final Exam Study Guide

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    QNT/561 Final Examination Study Guide This study guide will prepare you for the Final Examination you will complete in the final week. It contains practice questions‚ which are related to each week’s objectives. In addition‚ refer to each week’s readings and your student guide as study references for the Final Examination. Week One: Descriptive Statistics and Probability Distributions Objective: Compute descriptive statistics for given data sets. 1. In 1995‚ the cost of unleaded gasoline

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    had been taken up. Through DMAIC process initially 53 inputs were identified in Detailed Map‚ which was scaled down to 5 critical inputs after C&E Matrix and FMEA. Regression Analysis was done on real time data and best-fitted line were plotted to find out the effects of those critical inputs on hot metal silicon. Finally a Regression Equation was found and trial values approximately near to the calculated value of the

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    econ3208

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    statistics are given in Table 2.1 while the OLS regression results are given in Table 2.2. Please answer the following questions using the information in the tables. (i) Using the estimated results: (a) Carefully interpret all of the parameters in the regression model including their magnitudes and expected and actual signs. (b) Comment on the statistical significance of each of the estimated coefficients cigarette demand. (d) Suppose the regression model was re-estimated under the hypothesis

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    Managerial Report: Finding the Best Car Value I. Cost/Mile vs. Car Size Let us begin this report by examining how closely related Cost/Mile is to the Size of the car being tested. To do this‚ a multiple regression analysis was run using Cost/Mile as the dependent variable‚ and the ‘dummy’ variables Family-Sedan and Upscale-Sedan as independent variables. In examining the results‚ the first thing we notice is the “R Square” value is 0.7471. This represents the multiple coefficient of determination

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    Restaurant Rating

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    combining reviews from the website Yelp.com and restaurant data from the Washington State Department of Revenue. Because Yelp prominently displays a restaurant ’s rounded average rating‚ I can identify the causal impact of Yelp ratings on demand with a regression discontinuity framework that exploits Yelp‟s rounding thresholds. I present three findings about the impact of consumer reviews on the restaurant industry: (1) a one-star increase in Yelp rating leads to a 5-9 percent increase in revenue‚ (2) this

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    WGU MSN paper

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    BEC1 Study guide – Updated (please discard any other study guide currently in your possession and replace it with this one) – only 33 pages. Yah!!     Introduction (Chapter 1 – Munro e-book) Know the definition of population‚ sample‚ parameter‚ & statistic Be able to identify and/or provide examples of descriptive statistics & inferential statistics Know the properties of & be able to identify or provide examples of quantitative vs. categorical variables   Basic Concepts (Chapter 2 – Munro

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