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    Regression and Correlation

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    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 nonlinear

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    Uniform Hospital Discharge Data Set Veronica Burgos Kaplan University   The year was 1969‚ when a conference was held by the National Center for Health Services Research and Development and Johns Hopkins to address hospital discharge abstract systems. A hospital discharge abstract system is an “abstraction of minimum data set from hospital charts for the purpose of producing summary statistics about hospitalized patients” (Porta‚ 2014). During that conference participants discussed the possibility

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    Regression Analysis

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    to collect related data and prove the hearsay is rooted in fact or not. a) Chi-square Goodness-of-fit Tests on AT&T In order to test the validity of the hearsay‚ he collects 54 observations of monthly investment returns on AT&T and DJIA (Dow Jones Industrial Average) from March 2008 to September 2012. After gathering the data‚ he is going to test whether the number of months that has positive investment returns on AT&T are equal to months of negative returns. Therefore he sets a hypothesis; the

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    Bivariate Regression

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    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 about

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    National Bank of Pakistan [pic] Maryam Naeem MC080202354 MBA (HRM) Session-Feb 2008-Feb 2010 Submission Date: March 22‚ 2010 Virtual University of Pakistan [pic] Letter of Undertaking Internship Certificate: Dedication I dedicate this effort to my dear Grand Maa (Late) whose prayers made me able to reach where I am today. Thanks Amma!

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    sectors across. Information technology in recent years showed a complete revolution in how information is collected‚ stored/managed and used in both business and government around the world. The world and the workplace has been changed from working on paper documents which always face the problem of errors and delays‚ to the world of computers and information technology where work is carried out in its own way with accuracy and on time. Information technology can be even used to interconnect different

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    Regression Analysis

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    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 answered

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    Buckeye National Bank 1. a) PDOR- Est. MOH/Est. Act. (Total indirect costs/total value of checks processed) $2‚850‚000/$95‚000‚000= $0.03 per dollar processed. b) (i) Retail Line—(Value of checks processed X cost per dollar processed) $9‚500‚000 X $0.03= $285‚000 (ii) Business Line $85‚500‚000 X $0.03= $2‚565‚000 The allocations are driven by the dollar value of the checks processed. c) (i) Total indirect cost proportion for Retail Line (Allocation amount/Est. MOH) $285‚000/$2

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    linear regression

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    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 single

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    QUAKER NATIONAL BANK A Case Analysis Group # 5 July 29‚ 2013 I. POINT OF VIEW It is the point of view of the executive vice president of Quaker Bank – Mr. Matthew Killian. II. STATEMENT OF THE PROBLEM The crisis of the executive vice president – Mr. Killian is on how to properly manage risks of Quaker National Bank. III. AREAS OF CONSIDERATION First to consider is the bank’s judgment of the exposure to credit‚ interest rate and liquidity risk to be excessive in relation

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