Regression analysis Essays & Research Papers

Introduction This presentation on Regression Analysis will relate to a simple regression model. Initially, the regression model and the regression equation will be explored. As well, there will be a brief look into estimated regression equation. This case study that will be used involves a large Chinese Food restaurant chain. Business Case In this instance, the restaurant chain's management wants to determine the best locations in which to expand their restaurant business. So far the...

 Mortality Rates Regression Analysis of Multiple Variables Neil Bhatt 993569302 Sta 108 P. Burman 11 total pages The question being posed in this experiment is to understand whether or not pollution has an impact on the mortality rate. Taking data from 60 cities (n=60) where the responsive variable Y = mortality rate per population of 100,000, whose variables include Education, Percent of the population that is nonwhite, percent of population...

REGRESSION ANALYSIS Correlation only indicates the degree and direction of relationship between two variables. It does not, necessarily connote a cause-effect relationship. Even when there are grounds to believe the causal relationship exits, correlation does not tell us which variable is the cause and which, the effect. For example, the demand for a commodity and its price will generally be found to be correlated, but the question whether demand depends on price or vice-versa; will not be...

REGRESSION ANALYSIS (SIMPLE LINEAR REGRESSION) Submitted By Maqsood Khan MS - MANAGEMENT SCIENCES, 2nd SEMESTER Submitted TO GOHAR REHMAN ASSISTANT: PROFESSOR, SUIT Sarhad University Of Science And Information Technology Peshawar SESSION: 2012-13 TABLE OF CONTENTS |S. No. |Subjects |Page No. | |1 | |Introduction...

Regression Analysis is a very effective quantitative forecasting technique for short, medium and long range time horizons and can be easily updated and changed. Regression Analysis: presupposes that a linear relationship exists between one or more independent (casual) variables, which are predicted to affect the dependent(target) variable. Linearity: The observed relationship between the independent and dependent variables Example: A HR can use regression analysis to predict the number of...

Chapter 9 Regression Analysis 1. a. Y = 250 + 3 X b. Functional. For a given value of X there is one unique value of Y. 2. The model with the highest R2 might actually "overfit" the data and not provide accurate predictions. The R2 statistic can be inflated (or made arbitrarily large) by including superfluous independent variables in the model. If this happens the predictive ability of the model will actually be degraded since the model is biased toward sample specific anomalies in...

Regression Analysis (Tom’s Used Mustangs) Irving Campus GM 533: Applied Managerial Statistics 04/19/2012 Memo To: From: Date: April 19st, 2012 Re: Statistic Analysis on price settings Various hypothesis tests were compared as well as several multiple regressions in order to identify the factors that would manipulate the selling price of Ford Mustangs. The data being used contains observations on 35 used Mustangs and 10 different characteristics. The test hypothesis...

Regression Analysis Abstract Quantile regression. The Journal of Economic Perspectives This paper is formulated towards that of regression analysis use in the business world. The article used for this paper was written in order to understand the meaning of regression as a measurement tool and how the tool uses past business data for the purpose of future business economics. The research mentioned in this article pertained to quantile regression, or how percentiles of specific data are used...

Quantitative Methods Project Regression Analysis for the pricing of players in the Indian Premier League Executive Summary The selling price of players at IPL auction is affected by more than one factor. Most of these factors affect each other and still others impact the selling price only indirectly. The challenge of performing a multiple regression analysis on more than 25...

Confidence intervals and prediction intervals from simple linear regression The managers of an outdoor coffee stand in Coast City are examining the relationship between coffee sales and daily temperature. They have bivariate data detailing the stand's coffee sales (denoted by [pic], in dollars) and the maximum temperature (denoted by [pic], in degrees Fahrenheit) for each of [pic] randomly selected days during the past year. The least-squares regression equation computed from their data...

CASE STUDY: 1 The bulbs manufactured by a company gave a mean life of 3000 hours with standard deviation of 400 hours. If a bulb is selected at random, what is the probability it will have a mean life less than 2000 hours? Question: 1) Calculate the probability. 2) In what situation does one need probability theory? 3) Define the concept of sample space, sample points and events in context of probability theory. 4) What is the difference between objective and subjective...

 CHAPTER 13 CORRELATION AND REGRESSION ANALYSIS OUTLINE 4.1 Definition of Correlation Analysis 4.2 Scatter Diagram and Types of Relationships 4.3 Correlation Coefficient 4.4 Interpretation of Correlation Coefficient 4.5 Definition of Regression Analysis 4.6 Dependent and Independent Variables 4.7 Simple Linear Regression: Least Squares Method 4.8 Using the simple Linear Regression equation 4.9 Cautionary Notes and Limitations OBJECTIVES By the...

SALES REPRESENTATIVE | NUMBER OF UNITS SOLD | NUMBER OF SALES CALLS | A | 28 | 14 | B | 66 | 35 | C | 38 | 22 | D | 70 | 29 | E | 22 | 6 | F | 27 | 15 | G | 28 | 17 | H | 47 | 20 | I | 14 | 12 | J | 68 | 29 | | | | | | | a) draw a scatter diagram of number of sales calls and number of units sold b) Estimate a simple linear regression model to explain the relationship between number of sales calls and number of units sold y=2.139x-1.760 Number of...

Chapter3 Multiple Regression Analysis: Estimation Key drawback of SLR: all other factors affecting y are unrelated with x, as is unrealistic. Multiple regression allows us to control for many other factors to explain dependent variable, which is useful both for testing economic theories and for drawing the ceteris paribus conclusion. In addition, MR can incorporate fairly general functional form and build better models for predicting the regressand. Econometrics_buaa_Phd, Ma 1 3.1...

Introduction Team D will examine positive relationship of wages with multiple variables. The question is, are wages dependent on the gender, occupation, industry, years of education, race, years of work experience, marital status, and union membership. We will use the technique of linear regression and correlation. Regression analysis in this case should predict the value of the dependent variable (annual wages), using independent variables (gender, occupation, industry, years of education,...

 Correlation and regression are techniques which are used to see whether a relationship exists between two or more different sets of data Learning Objectives: To identify, by diagram, whether a possible relationship exists between two variables; To quantify the strength of association between variables using the correlation coefficient; To show how a relationship can be expressed as an equation; To identify linear equations when written and when graphed; To examine...

BRUNEL UNIVERSITY Master of Science Degree examination Specimen Exam Paper 2005-2006 EC5002: Modelling Financial Decisions and Markets EC5030: Introduction to Quantitative Methods Time allowed: 1.5 hours Answer all of question 1 and at least two other questions 1. COMPULSORY Provide brief answers to all the following: (a) A sample of 20 observations corresponding to the model: Y = + X + u, gave the P P P following data: (X X)2 = 215:4, (Y Y )2 = 86:9, and (X X)(Y Y ) = 106:04. Estimate . (5...

Seth Hill Professor Gwinn Econometrics March 3, 2011 Unemployment Rate and Total New Houses Sold For decades, owning a home has been touted as the very heart of "the American Dream", but today that dream is out of reach for an increasing number of Americans. Why? It is because there are not nearly enough jobs for everyone. Without a jobs recovery, there simply is not going to be a housing recovery. In this report, I will perform a regression analysis to determine the effect of the...

1. If the correlation coefficient between the variables is 0, it means that the two variables aren’t related. – TRUE 2. In a simple regression analysis the error terms are assumed to be independent and normally distributed with zero mean and constant variance. – TRUE 3. The difference between the actual Y-value and the predicted Y-value found using a regression equation is called the residual (ε) – TRUE 4. In a multiple regression analysis with N observations and k independent...

Econometric project Introduction Mutual funds are the name of open-end investment companies, which collect a pool of funds from individual investors to invest in securities such as bonds, stocks or other assets. The main advantages of mutual funds are diversification and professional management. However, if the mangers lack the ability to outperform the market index, individual investors will lose invests. Therefore, it is important for individual investors...

AJ DAVIS Generate a scatterplot for CREDIT BALANCE vs. SIZE, including the graph of the "best fit" line. Interpret. Determine the equation of the "best fit" line, which describes the relationship between CREDIT BALANCE and SIZE 2591+ 403.221 Determine the coefficient of correlation. Interpret. .75/ r-sq(56.6%). There is a mild correlation. Determine the coefficient of determination. Interpret. 56.6% Test the utility of this regression model (use a two tail test with α =.05)....

Updated: November 11, 2011 Lecturer: Thilo Klein Contact: tk375@cam.ac.uk Contest Quiz 6 Question Sheet In this quiz we will review non-linearity and model transformations covered in lectures 6 and 7. Question 1: Logarithms (i) The interpretation of the slope coefficient in the model Yi = β0 + β1 ln(Xi ) + ui is as follows: (a) a 1% change in X is associated with a β1 % change in Y. (b) a 1% change in X is associated with a change in Y of 0.01 β1 . (c) a change in X by one unit is associated...

Javier Jorge Dr. Moss Managerial Analysis April 11th, 2012 Project 3 We are given a linear regression that gives us an equation on the relationship of Quantity on Total Cost. As stated in the project, the regression data is very good with a relatively high R2, significant F, and t-values but we can’t use this model to estimate plant size. When we perform a simple eye test on the residual plot for Q a trend seems to form from positive to negative and back to positive. When we...

Econometric Homework 8 M10118108 蘇裕翔 M10118116 張哲維 Example 7.12 以二元變數 arr86 代表一個人被逮捕的情況，自變數 pcnv 為先逮捕後判罪的比例，avgsen 為平均服刑的時間（月），tottime 為1986年以前滿18歲罪犯之總服刑時間（月），ptime86 為1986年之服刑時間（月），qemp86 為1986年度合法被雇用之季數。估計式如下： arr86=0.441-0.162pcnv+0.0061avgsen-0.0023tottime-0.022ptime86-0.043qemp86 　　　0.017 0.021 0.0065 0.005 n=2,725,　R2=0.0474 (1) 截距項表示此人在1986年處於無工作狀態、無任何前科紀錄、18歲後且1986年完全沒有坐牢的紀錄等情況下之被逮捕機率，其估計之機率約為 0.441。 (2) 當 pcnv 由0變成1時，表示從不可能被判刑到確定判刑的改變，當 pcnv 增加0.5個單位，會使得被逮捕機率降低約...

STA9708 Regression Analysis: Literacy rates and Poverty rates As we are aware, poverty rate serve as an indicator for a number of causes in the world. Poverty rates are linked with infant mortality, education, child labor and crime etc. In this project, I will apply the regression analysis learned in the Statistics course to study the relationship between literacy rates and poverty rates among different states in USA. In my study, the poverty rates will be the independent variable (x) and...

MULTIPLE REGRESSION After completing this chapter, you should be able to: understand model building using multiple regression analysis apply multiple regression analysis to business decision-making situations analyze and interpret the computer output for a multiple regression model test the significance of the independent variables in a multiple regression model use variable transformations to model nonlinear relationships recognize potential problems in multiple...

Question 1: Run the regression Report your answer in the format of equation 5.8 (Chapter 5, p. 152) in the textbook including and the standard error of the regression (SER). Interpret the estimated slope parameter for LOT. In the interpretation, please note that PRICE is measured in thousands of dollars and LOT is measured in acres. Model 1: OLS estimates using the 832 observations 1-832 Dependent variable: price VARIABLE COEFFICIENT STDERROR T STAT P-VALUE...

Project 1: Linear Correlation and Regression Analysis Gross Revenue and TV advertising: Pfizer Inc, along with other pharmaceutical companies, has begun investing more promotion dollars into television advertising. Data collected over a two year period, shows the amount of money Pfizer spent on television advertising and the revenue generated, all on a monthly bases. |Month |TV advertising |Gross Revenue | |1 |17 |4.1 | |2...

Effect of Ratio Profitability: Return on Asset (ROA) and Return of Equity (ROE) to Stock Price of PT Bank Central Asia (BCA) Tbk. Ratio profitability, Return on Asset (ROA) and Return of Equity (ROE), of a firm is used as one of parameters for investor to decide whether they want to invest or not. The following table consists of ROA and ROE as well as the stock price of PT Bank Central Asia (BCA) Tbk., as one of the largest bank in Indonesia, from year of 2002 up to 2011. Table 1. ROA, ROE...

Data Log(Attendance) = B1wins + B2FCI + B3tktprice + B4payroll + B5state + B6earnspop In order to explain the effect that winnings percentage has on attendance, I have created an adjusted economic model that I have specified above. In order to test my economic model, I have compiled data for each of the variables specified in the model from the years 2003 to 2005. The question that I will be answering in my regression analysis is whether or not wins have an affect on attendance in...

Instructor Solutions Manual to accompany Applied Linear Statistical Models Fifth Edition Michael H. Kutner Emory University Christopher J. Nachtsheim University of Minnesota John Neter University of Georgia William Li University of Minnesota 2005 McGraw-Hill/Irwin Chicago, IL Boston, MA PREFACE This Solutions Manual gives intermediate and final numerical results for all end-of-chapter Problems, Exercises, and Projects with computational elements contained in Applied Linear Statistical...

Regression Analysis of Army Jackboots Ochirmunkh Boldbaatar, Myriam Hirscher, Bastian Latz, and Manuel Padutsch ECON 510 Aun Hassan November 26, 2012 Introduction The German company we established the data from sells cloths and shoes. The customers are not private customers but mostly national divisions like the military or fire departments. The company has around 20 stores in Germany; however, the stores have different prices for the same products. The data package we received...

Introduction The number of empirical work studying house prices and their links to the other factors are persistently on the rise. Housing market research has been topical since its role in the recent global economic crisis, specifically referring to the recent boom in house prices in many developed countries following a sharp bust in 2008. Researches and policy makers alike have realized that housing has significant influences on the business cycle. This paper tries to figure out the...

BUSI 410 Business Analytics Module 22: Revitalizing Dell 1 Last lecture • Home Depot revenue (forecasting) • Using correlation to choose lag • Using Durbin-Watson statistic to test missing drivers • Out-of-sample model validation 2 Dell’s success strategies • Direct model (marketing) – “Cut out the middlemen.” – NC born Harlem drug lord Frank Lucas • Mass customization (design) – Modularity – Component commonality – Postponement • Lean manufacturing (operations) –...

QUANTITATIVE METHODS:- Quantitative methods of forecasting include ASSOCIATIVE (CAUSAL) MODELS:- There is a causal relationship between the variable to be forecast and another variable or a series of variables. (Demand is based on the policy, e.g. cement, and build material. Causal Model: Demand for next period = f (number of permits, number of loan application....) There is no logical link between the demand in the future and what has happened in the past. There are other factors which...

The business question that I am addressing is whether the price (y-intercept) of a sample of used cars (n=50) has a relationship with the independent variables miles (k), mpg, year, and engine type. The best univariate technique to predict the value of (y) is the mean, which is $26, 268. The best technique to measure the y-intercept is how many miles (k) the used car has been driven by the previous owner. This was found by measuring the strongest correlation between price and the independent...

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...

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...

Determinants of Production and Consumptions Determinants of Industry Production (Supply) Supply is the amount of output of production that producers are willing and able to sell at a given price all other factors being held constant. The following are the determinants of supply: Price (P), Numbers of Producers (NP), Taxes (T) Model Specification Specification of model is to specify the form of equation, or regression relation that indicates the relationship...

Regression Analysis of Pricing of IPL Players | Project Report | | | | | Pricing of Players in the Indian Premier League Executive Summary In the project, price for the players in IPL are analysed against various factors. Not all factors drove the price of a player were directly related to their performance on the field, whereas there are specific factors which had a direct impact on player’s remuneration. These factors ranged from performance measure of players such as...

 Contents 1.0 Introduction and Motivation 2 2.0 Methodology 5 2.1. Descriptive Statistics 5 2.2 Matrix of pairwise correlation. 6 3.0 Model Specification 6 3.1 Linear Regression Model. 6 3.2 The Regression Specification Error Test 8 3.3 Non-linear models 9 3.4 Autocorrelation. 10 3.5 Heteroskedasticity Test 10 4.0 Hypothesis Testing 11 5.0 Binary (Dummy) Variables 11 6.0 Conclusion 13 Reference List 13 1.0 Introduction and Motivation Crude oil is one of the world’s most important...

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...

淡江大學運輸管理學系 101(2): 2nd Semester, 2013 運輸經濟(二) Transportation Economics Assignment #1 Due: March 21, 2013 1. (40%) Transportation Demand Analysis Application Background: 新北市「淡水捷運延伸線輕軌運輸系統」，即淡水捷運延伸至淡海新市鎮之輕軌 捷運系統，此線原先由臺北市政府捷運工程局規劃，後來因淡海新市鎮未完全開 發，興建上無迫切性，故該案被裁定暫以公車接駁方式暫行之為佳。目前為配合 內政部營建署調整淡海新市鎮之建設及帶動當地發展，由交通部高速鐵路工程局 重新推動本計劃。目前淡水捷運延伸線可行性研究報告書已經由行政院核定，原 則同意綠山線及藍海線之路網，並優先推動綠山線。高鐵局刻正辦理綜合規劃複 審與環評複審相關作業。 Problem: 針對「淡海輕軌捷運」可行性評估，首要工作為未來的旅運需求分析與預測，試 說明與研擬如何進行淡海輕軌捷運系統的旅運需求分析步驟與架構，須蒐集、調...

Chap 13 44 1.4 100 1.3 110 1.3 110 0.8 85 1.2 105 1.2 105 1.1 120 0.9 75 1.4 80 1.1 70 1.0 105 1.1 95 A sample of 12 homes sold last week in St. Paul, Minnesota, is selected. Can we conclude that, as the size of the home (reported below in thousands of square feet) increases, the selling price (reported in $ thousands) also increases? * Compute the coefficient of correlation. * = [12(1344) – (13.8)(1160)]/12(16.26) –...

Linear Regression & Best Line Analysis Linear regression is used to make predictions about a single value. Linear regression involves discovering the equation for a line that most nearly fits the given data. That linear equation is then used to predict values for the data. A popular method of using the Linear Regression is to construct Linear Regression Channel lines. Developed by Gilbert Raff, the channel is constructed by plotting two parallel, middle lines above and below a Linear...

DETERMINANTS AND ECONOMIC CONSEQUENCES OF COLONIZATION: A GLOBAL ANALYSIS Arhan S. Ertan, Louis Putterman Abstract Existing research in the area of economic growth suggests that the era of colonization has had an impact upon the modern levels of economic development of countries around the globe. However, why some countries were colonized early, some late, and others not at all, and what effect these differences have on current national income, has not been studied systematically. In the first...

Demand Forecasting Problems Simple Regression a) RCB manufacturers black & white television sets for overseas markets. Annual exports in thousands of units are tabulated below for the past 6 years. Given the long term decline in exports, forecast the expected number of units to be exported next year. |Year |Exports |Year |Exports | |1 |33 |4...

 F-2,Block, Amity Campus Sec-125, Nodia (UP) India 201303 ASSIGNMENTS PROGRAM: SEMESTER-I Subject Name : Study COUNTRY : Permanent Enrollment Number (PEN) : Roll Number : Student Name : INSTRUCTIONS a) Students are required to submit all three assignment sets. ASSIGNMENT DETAILS MARKS Assignment A Five...

Introduction to Statistical Methods AD-40-23 All the assignments are to be handed in the classroom one week after the Session where the corresponding subjects are treated. Assignments sent via internet will not be considered. Session 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...

Introduction: The main idea of a multiple regression analysis is to understand the relationship between several independent variables and a single dependent variable. (Lind, 2004) A model of the relationship is hypothesized, and estimates of the parameter values are used to develop an estimated regression equation.(abyss.uoregon.edu) The multiple regression equation used to describe the relationship is: Y' = a + b1X1 + b2X2 + b3X3 +……. + bkXk. It is used to estimate Y given selected X values...

 Contents 1.0 Introduction and Motivation 2 2.0 Methodology 5 2.1. Descriptive Statistics 5 2.2 Matrix of pairwise correlation. 6 3.0 Model Specification 6 3.1 Linear Regression Model. 6 3.2 The Regression Specification Error Test 8 3.3 Non-linear models 9 3.4 Autocorrelation. 10 3.5 Heteroskedasticity Test 10 4.0 Hypothesis Testing 11 5.0 Binary (Dummy) Variables 11 6.0 Conclusion 13 Reference List 13 1.0 Introduction and Motivation Crude oil is one of the world’s most important...

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CHAPTER 4: FORECASTING TRUE/FALSE 1. Tupperware only uses both qualitative and quantitative forecasting techniques, culminating in a final forecast that is the consensus of all participating managers. False (Global company profile: Tupperware Corporation, moderate) 2. The forecasting time horizon and the forecasting techniques used tend to vary over the life cycle of a product. True (What is forecasting? moderate) 3. Sales forecasts are an input to financial planning, while demand...

Regression Analysis (First Mid-term Exam) 10/25/2012 i.i.d. 1. Consider the model Yi =β 0 + β1 xi2 + ε i , ε i ~ N (0, σ 2 ) . (a) (12%) Write down the normal equation and find the least squares estimators of β 0 and β1 . (b) (9%) Define ei , and show that ∑e i = 0 . Is it necessarily true that i ∑e x i i = 0 ? Why i or why not? (c) (5%) Find an estimator of σ 2 . What is the degree of freedom associated with the estimator? i.i.d. 2. Given that Yi =β 0 + β1 xi + ε i , ε i ~ N (0, σ 2...

MULTIPLE REGRESSION ANALYSIS USING DUMMY VARIABLE HDI Regression Using Health, Education &Income 3/21/2012 Department Of Business Economics Jasmine Kaur(598) Kshama (577) Maanya Kaushik ShikhaChaurasia(600) ABSTRACT In this project we have employed tools of empirical econometric analysis to examine the relationship between the Human Development Index and the indicators of Human Development. Table of contents...

Regression Analysis: Predicting for Detroit Tigers Game Managerial Economics BSNS 6130 December 13, 2012 By: Morgan Thomas Chad Goodrich Jake Dodson Austin Burris Brittany Lutz Abstract As there are many who invest in athletic events, the ability to better predict attendance to such events, such as the Detroit Tigers games, could benefit many. The benefits include being able to better stock concessions stands, allocate advertising budgets, and staff security. Therefore, the...

Quick Stab Collection Agency: A Regression Analysis Gerald P. Ifurung 04/11/2011 Keller School of Management Executive Summary Every portfolio has a set of delinquent customers who do not make their payments on time. The financial institution has to undertake collection activities on these customers to recover the amounts due. A lot of collection resources are wasted on customers who are difficult or impossible to recover. Predictive analytics can help optimize the allocation of...

 2008: H0: The variables will predict whether or not a team will make the playoffs. H1: The variables will not predict whether or not a team will make the playoffs. After running the regressions, it’s clear that all of the variables are insignificant at the 5% level. The only one that may have some significance is the rush rank, yet even that variable is not a great indicator of whether or not a team will make the playoffs. The relationship between rush rank and making the playoffs is...

Tiffany Camp ECO-250 Volker Grzimek Regression Analysis of Work Hours in Relation to GPA This research investigated the affects of working extra hours in a labor position on students’ GPAs each semester at Berea College. It was my belief that students who worked more hours were more likely to have lower GPAs due to their studying abilities and opportunities being compromised as a result of working too long (a negative correlation or trend between GPAs and hours worked each week)....

IBA134 Business Statistics OUA Study Period 2 (SP2), 2013 Computer Assignment (Worth 15% of the overall assessment for the unit) Due date: 5pm (QLD time) on Sunday 11, August 2013 Instructions: • All numerical calculations and graphs/plots should be done using EXCEL. • A hard copy of your completed assignment must be submitted electronically with the Griffith OUA Cover Sheet (available in the Assessment section of the unit website) attached as the 1st...

ESSAYS ON POVERTY, MICROFINANCE AND LABOR ECONOMICS by SANDARADURA INDUNIL UDAYANGA DE SILVA, B.Sc., M.A. A DISSERTATION IN ECONOMICS Submitted to the Graduate Faculty of Texas Tech University in Partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY Approved Masha Rahnama Chairperson of the Committee Thomas Steinmeier Robert McComb Accepted John Borrelli Dean of the Graduate School August, 2006 Copyright 2006, Sandaradura Indunil Udayanga De Silva...

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...

 Regression Analysis for Strike with Damage Reported and Wildlife Strike II. ABSTRACT A wildlife strike into aircraft engines at takeoff and/or landing causes highly significant outcomes. The Federal Aviation Administration released Advisory Circular (FAA, AC150/5200-32B, 2013) to address importance of the reporting and encourage airline operators to report wildlife strike damage. The FAA conducted a study of wildlife strike reporting systems in mid 1990s and used a...

 MATH533: Applied Managerial Statistics PROJECT PART C: Regression and Correlation Analysis Using MINITAB perform the regression and correlation analysis for the data on SALES (Y) and CALLS (X), by answering the following questions: 1. Generate a scatterplot for SALES vs. CALLS, including the graph of the "best fit" line. Interpret. After interpreting the scatter plot, it is evident that the slope of the ‘best fit’ line is positive, which indicates that sales amount varies...

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...

Multiple regression, a time-honored technique going back to Pearson's 1908 use of it, is employed to account for (predict) the variance in an interval dependent, based on linear combinations of interval, dichotomous, or dummy independent variables. Multiple regression can establish that a set of independent variables explains a proportion of the variance in a dependent variable at a significant level (through a significance test of R2), and can establish the relative predictive importance...

Chapter 13 Linear Regression and Correlation True/False 1. If a scatter diagram shows very little scatter about a straight line drawn through the plots, it indicates a rather weak correlation. Answer: False Difficulty: Easy Goal: 1 2. A scatter diagram is a chart that portrays the correlation between a dependent variable and an independent variable. Answer: True Difficulty: Easy Goal: 1 AACSB: AS 3. An economist is interested in...

1 CORRELATION & REGRESSION 1.0 Introduction Correlation and regression are concerned with measuring the linear relationship between two variables. 1.1 Scattergram It is not a graph at all, it looks at first glance like a series of dots placed haphazardly on a sheet of graph paper. The purpose of scattergram is to illustrate diagrammatically any relationship between two variables. (a) If the variables are related, what kind of relationship it is, linear or...

Multiple Regression Analysis of exchange rate with the determinant factors Regression Analysis: USD versus GDP Growth, FER, FDI Growth, Interest Rate, Money Supply, Terms Of Trade The regression equation is USD = 41.5 - 1.95 GDP Growth + 0.000943 FER - 0.139 FDI Growth + 0.048 Differential Interest Rate + 0.000067 Money Supply + 0.166 Terms of Trade - 0.000097 External Debt | Predictor T PConstant...

Assignment Week 1 Answer the following questions: 1. Describe the rationale for utilizing probability concepts. For practical reasons, variables are observed to collect data. The sampled data is then analyzed to elicit information for decision making in business and indeed in all human endeavors. However, sampled information is incomplete and not free from sampling error. Its use in decision-making processes introduces an element of chance. Therefore, it is important for a...

Linear ------------------------------------------------- Important EXERCISE 27 SIMPLE LINEAR REGRESSION STATISTICAL TECHNIQUE IN REVIEW Linear regression provides a means to estimate or predict the value of a dependent variable based on the value of one or more independent variables. The regression equation is a mathematical expression of a causal proposition emerging from a theoretical framework. The linkage between the theoretical statement and the equation is made prior to data...

REGRESSION ANALYSIS Prediction of growth rate on the basis of other economic variables Prepared by Richa Srivastava GSB Summer 2012 Index 1 2 3 4 5 6 7 8 Description of the Analysis Calculation of descriptive statistics Initial regression run Regression Run-II Regression Run-III Regression Run-IV Graphical Representation Ex-Post Simulation Introduction The level of economic growth for a particular country is a combination of many economic aspects. There are several macroeconomic and...

Simple Linear Regression in SPSS 1. STAT 314 Ten Corvettes between 1 and 6 years old were randomly selected from last year’s sales records in Virginia Beach, Virginia. The following data were obtained, where x denotes age, in years, and y denotes sales price, in hundreds of dollars. x y a. b. c. d. e. f. g. h. i. j. k. l. m. 6 125 6 115 6 130 4 160 2 219 5 150 4 190 5 163 1 260 2 260 Graph the data in a scatterplot to determine if there is a possible linear relationship. Compute and...

Multiple regression: OLS method (Mostly from Maddala) The Ordinary Least Squares method of estimation can easily be extended to models involving two or more explanatory variables, though the algebra becomes progressively more complex. In fact, when dealing with the general regression problem with a large number of variables, we use matrix algebra, but that is beyond the scope of this course. We illustrate the case of two explanatory variables, X1 and X2, with Y the dependant variable....

Limitations: Regression analysis is a commonly used tool for companies to make predictions based on certain variables. Even though it is very common there are still limitations that arise when producing the regression, which can skew the results. The Number of Variables: The first limitation that we noticed in our regression model is the number of variables that we used. The more companies that you have to compare the greater the chance your model will be significant. We have found...

Topic 8: Multiple Regression Answer a. Scatterplot 120 Game Attendance 100 80 60 40 20 0 0 5,000 10,000 15,000 20,000 25,000 Team Win/Loss % There appears to be a positive linear relationship between team win/loss percentage and game attendance. There appears to be a positive linear relationship between opponent win/loss percentage and game attendance. There appears to be a positive linear relationship between games played and game attendance. There does not appear to be any...

Linear-Regression Analysis Introduction Whitner Autoplex located in Raytown, Missouri, is one of the AutoUSA dealerships. Whitner Autoplex includes Pontiac, GMC, and Buick franchises as well as a BMW store. Using data found on the AutoUSA website, Team D will use Linear Regression Analysis to determine whether the purchase price of a vehicle purchased from Whitner Autoplex increases as the age of the consumer purchasing the vehicle increases. The data set provided information about the...

 Term Paper Data: Diamond Earrings Model: Multiple Regression The paper is trying to find a relationship between the variables Price of Diamond Earrings and Carat, Color, and Clarity of diamonds used in the earrings. For the analysis the technique of Multiple Linear Regression has been used and checked the validity of the fitted model. Table of Contents Introduction: Diamond earrings are the most expensive gifts those bought by one...

 CORRELATION Md. Musa Khan Lecturer DBA, IIUC musa_stat@yahoo.com Definition: If two or more...

 linear regression In statistics, linear regression is an approach to model the relationship between a scalar dependent variable y and one or more explanatory variables denoted X. The case of one explanatory variable is called simple linear regression. For more than one explanatory variable, it is called multiple linear regression. (This term should be distinguished from multivariate linear regression, where multiple correlated dependent variables are predicted,[citation needed] rather than a...

Linear Regression deals with the numerical measures to express the relationship between two variables. Relationships between variables can either be strong or weak or even direct or inverse. A few examples may be the amount McDonald’s spends on advertising per month and the amount of total sales in a month. Additionally the amount of study time one puts toward this statistics in comparison to the grades they receive may be analyzed using the regression method. The formal definition of Regression...

Nonlinear regression From Wikipedia, the free encyclopedia Regression analysis Linear regression.svg Models Linear regression Simple regression Ordinary least squares Polynomial regression General linear model Generalized linear model Discrete choice Logistic regression Multinomial logit Mixed logit Probit Multinomial probit Ordered logit Ordered probit Poisson Multilevel model Fixed effects Random effects Mixed model Nonlinear regression Nonparametric Semiparametric Robust Quantile...

Scatter Plots Linear regression is a crucial tool in identifying and defining key elements influencing data. Essentially, the researcher is using past data to predict future direction. Regression allows you to dissect and further investigate how certain variables affect your potential output. Once data has been received this information can be used to help predict future results. Regression is a form of forecasting that determines the value of an element on a particular situation....

Types of regression and linear regression equation 1. The term regression was first used as a statistical concept in 1877 by Sir Francis Galton. 2. Regression determines ‘cause and effect’ relationship between variables, so it can aid to the decision-making process. 3. It can only indicate how or to what extent variables are associated with each other. 4. There are two types of variables used in regression analysis i.e. The known variable is called as Independent Variable and the variable...

Poisson Regression This page shows an example of poisson regression analysis with footnotes explaining the output. The data collected were academic information on 316 students. The response variable is days absent during the school year (daysabs), from which we explore its relationship with math standardized tests score (mathnce), language standardized tests score (langnce) and gender . As assumed for a Poisson model our response variable is a count variable and each subject has the same...

Keller Graduate School of Business Management Masters of Business Administration Regression Project Estimating Stock Prices of Independent E&P Companies Assignment for Course: HR 533, Applied Managerial Statistics Submitted to: Professor Mohamed Nayebpour Submitted by: Leah A. O’Daniels Location of Course: Blended – Houston Campus & On-line Date of Submission: December 16, 2011 Regression Analysis: StockPrice versus Sales(B) The regression equation is StockPrice...

Topic 4. Multiple regression Aims • Explain the meaning of partial regression coefficient and calculate and interpret multiple regression models • Derive and interpret the multiple coefficient of determination R2and explain its relationship with the the adjusted R2 • Apply interval estimation and tests of significance to individual partial regression coefficients d d l ff • Test the significance of the whole model (F-test) Introduction • The basic multiple regression model is a simple...

0905-section2.QX5 7/12/04 4:10 PM Page 140 13 Multiple regression Multiple regression In this chapter I will briefly outline how to use SPSS for Windows to run multiple regression analyses. This is a very simplified outline. It is important that you do more reading on multiple regression before using it in your own research. A good reference is Chapter 5 in Tabachanick and Fiddell (2001), which covers the underlying theory, the different types of multiple regression analyses and the...

EPI/STA 553 Principles of Statistical Inference II Fall 2006 Regression: Testing Assumptions December 4, 2006 Linearity The linearity of the regression mean can be examined visually by plots of the residuals against any of the independent variables, or against the predicted values. Chart 1 shows a residual plot that reveals no Chart 2 C hart 1 0.4 0.4 0.3 0.3 0.2 0.1 0.1 Residual Residual 0.2 0.0 -0.1 0.0 -0.1 -0.2 -0.2 -0.3 -0.3 -0.4...

Logistic regression In statistics, logistic regression, or logit regression, is a type of probabilistic statistical classification model.[1] It is also used to predict a binary response from a binary predictor, used for predicting the outcome of acategorical dependent variable (i.e., a class label) based on one or more predictor variables (features). That is, it is used in estimating the parameters of a qualitative response model. The probabilities describing the possible outcomes of a single...

 A. DETERMINE IF BLOOD FLOW CAN PREDICT ARTIRIAL OXYGEN. 1. Always start with scatter plot to see if the data is linear (i.e. if the relationship between y and x is linear). Next perform residual analysis and test for violation of assumptions. (Let y = arterial oxygen and x = blood flow). twoway (scatter y x) (lfit y x) regress y x rvpplot x 2. Since regression diagnostics failed, we transform our data. Ratio transformation was used to generate the dependent variable and...

Linear Regression Models 1 SPSS for Windows® Intermediate & Advanced Applied Statistics Zayed University Office of Research SPSS for Windows® Workshop Series Presented by Dr. Maher Khelifa Associate Professor Department of Humanities and Social Sciences College of Arts and Sciences © Dr. Maher Khelifa 2 Bi-variate Linear Regression (Simple Linear Regression) © Dr. Maher Khelifa Understanding Bivariate Linear Regression 3  Many statistical indices summarize information...

Understanding the Factors Affecting The Unemployment Rate Through Regression Analysis An Individual Report Presented to The Faculty of Economics Department In Partial Fulfillment To The Requirements for ECONMET C31 Submitted to: Dr. Cesar Rufino Submitted by: Aaron John Dee 10933557 April 8, 2011 1 TABLE OF CONTENTS I. INTRODUCTION A. Background of the Study B. Statement of the Problem C. Objective II. THEORETICAL FRAMEWORK AND RELATED LITERATURE A. GDP B. Average Years in...

Cox Regression Models Questions with Answers Worked Example An investigation is carried out into popularity of new cars being bought in the showroom of a Mercedes dealer. Data recorded for each car included colour, engine size and car type. A Cox proportional hazards model was fitted to the data and the results are given below: Write down the Cox hazard function according to this model. With regards to the model you have written down above state the following: • To which class of car does...

ABM PROJECT 2013 1. INTRODUCTION AND SUMMARY OF RESEARCH HYPOTHESIS It is common knowledge that the prices people have to pay for accommodation in hotels vary enormously. Furthermore, hotel revenue managers probably posses or more or less accurate intuition of what causes room rates to diverge. However, they do not know how Online Travel Agent sites select the leading hotels to be placed on their first search page. In this respect, some determinants are expected to be associated...

 Graduate School of Business Master in Business Administration Term paper requirement for Quantitative Techniques in Management Using Statistical Tool Analysing House Price Construction in Luzon Using Multiple Regression Analysis January 2014 Abstract This paper illustrates how Multiple Regression Analysis been used in explaining price variationfor selected houses. Each attribute that theoretically identified as price determinant is...