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16 results for "logistic regression"
Simple Predictive Analytics By Curtis Seare
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This book teaches the fundamentals of statistical business analysis by using the familiar program Excel 2007. With the help of this guide, you will be able to use Excel to solve your business... More > problems through the use of predictive analytics. The book includes: An introduction to, and some fundamentals for, good analysis, a process outline to make analysis quick and effective, a description of some of the most used predictive models and methods, and a comprehensive ‘How To’ section including a step by step Excel tutorial and common pitfalls to avoid.< Less
Simple Predictive Analytics By Curtis Seare
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This book teaches the fundamentals of statistical business analysis by using the familiar program Excel 2007. With the help of this guide, you will be able to use Excel to solve your business... More > problems through the use of predictive analytics. The book includes: An introduction to, and some fundamentals for, good analysis, a process outline to make analysis quick and effective, a description of some of the most used predictive models and methods, and a comprehensive ‘How To’ section including a step by step Excel tutorial and common pitfalls to avoid.< Less
Predictive Modeling and Analytics By Jeffrey Strickland
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This book is about predictive modeling. Yet, each chapter could easily be handled by an entire volume of its own. So one might think of this as a survey of predictive models, both statistical and... More > machine learning. We define A predictive model as a statistical model or machine learning model used to predict future behavior based on past behavior. In order to use this book, the reader should have a basic understanding of statistics (statistical inference, models, tests, etc.)—this is an advanced book. Every chapter culminates in an example using R. R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. The book is organized so that statistical models are presented first (hopefully in a logical order), followed by machine learning models, and then applications: uplift modeling and time series. One could use this as a textbook with problem solving in R (there are no “by-hand” exercises).< Less
OTREC-RR-10-13 By Christopher Monsere
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Traffic oscillations are typical features of congested traffic flow that are characterized by recurring decelerations followed by accelerations (stop-and-go driving). This report describes the... More > impact of freeway traffic oscillations on traffic safety. This study employs a matched case-control design using high resolution traffic and crash data from a freeway segment. Traffic conditions prior to each crash were taken as cases, while traffic conditions during the same periods on days without crashes were taken as controls. These were also matched by presence of congestion, geometry and weather; 82 cases were extracted from data from 2004 to 2007. Conditional logistic regression models were developed based on the case-control samples. The results reveal that the standard deviation of speed (thus, oscillations) is a significant variable. The average traffic states prior to crashes were less significant than the speed variations in congestion.< Less
OTREC-RR-10-13 By Christopher Monsere
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Traffic oscillations are typical features of congested traffic flow that are characterized by recurring decelerations followed by accelerations (stop-and-go driving). This report describes the... More > impact of freeway traffic oscillations on traffic safety. This study employs a matched case-control design using high resolution traffic and crash data from a freeway segment. Traffic conditions prior to each crash were taken as cases, while traffic conditions during the same periods on days without crashes were taken as controls. These were also matched by presence of congestion, geometry and weather; 82 cases were extracted from data from 2004 to 2007. Conditional logistic regression models were developed based on the case-control samples. The results reveal that the standard deviation of speed (thus, oscillations) is a significant variable. The average traffic states prior to crashes were less significant than the speed variations in congestion.< Less
Breaking Broken Windows: A Multivariate Approach to the Effects of Crime and Urban Decline By Emily J. Moore
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Broken windows theory suggests that neighborhood disorder, including physical deterioration and large-scale accumulations of graffiti and trash, routinely occur in many urban communities. Research on... More > community disorder suggests that signs of community disorganization and decay increase individuals’ perceived risks of criminal victimization and their subsequent fear of crime. The purpose of this study is to determine whether certain conditions found within communities have an effect on an individual’s level of fear.< Less
Breaking Broken Windows: A Multivariate Approach to the Effects of Crime and Urban Decline By Emily J. Moore
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Broken windows theory suggests that neighborhood disorder, including physical deterioration and large-scale accumulations of graffiti and trash, routinely occur in many urban communities. Research on... More > community disorder suggests that signs of community disorganization and decay increase individuals’ perceived risks of criminal victimization and their subsequent fear of crime. The purpose of this study is to determine whether certain conditions found within communities have an effect on an individual’s level of fear.< Less
Credit Risk Scorecards: Development and Implementation Using SAS By Mamdouh Refaat
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This book provides a systematic presentation of credit risk scorecard development and implementation. The text covers the theoretical foundations, the practical implementation and programming using... More > SAS. The book topics include : • Data acquisition - data preparation • EDA, predictive measures and variable selection • Optimal segmentation and binning • Coarse classing and WOE transformations • Development of logistic regression models • Methods of model assessment and evaluation • Scorecard creation and scaling • Automatic generation of scoring code (SAS, SQL, C) • Scorecard monitoring and reporting • Reject inference The SAS implementation contains over 50 ready-to-use SAS macros that can be implemented in the automation of the scorecard creation process.< Less
OCCUPATION-RELATED SUICIDE By Laurel Milwid
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There is a deficit in explanation for occupational differences in suicide-risk in the UK. Two studies of occupation-related suicide are unusual in reporting suicide-data for multiple occupations, but... More > do not incorporate demographic controls. A significant US study is, by contrast, based on a logistic regression model of analysis, with controls for demographic variables. The feasibility of developing a statistical model analogous to that of the US study, for testing with mortality data for England & Wales, depends on access to individual-level mortality data. The author's quest for access to this data revealed that Census-based and vital-events data are protected by the Census Act and the Population (Statistics) Act. In the US, by contrast, accessibility of such data to the public is mandated. A discussion of the legislation underlying the different mortality-data privacy-policies in the UK and the US gives rise to the question: To what extent do the dead need protection?< Less
Essentials of Statistics with SPSS By Scott Macdonald
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This textbook is designed to provide a good grounding of the most commonly used analytic approaches in the health sciences, using the Statistical Package for the Social Sciences (SPSS). Topics... More > covered include creation of a database, aggregation of data, data transformations, scale development, t-tests, cross tabulations, ANOVA, logistic regression, correlation and regression. Notes and slides are included in each Chapter that describe the essentials of each analytic approach. As well, data from the Canadian Community Health Survey are analyzed to illustrate the application of each approach. SPSS output is included, with the most important elements for a research paper highlighted and interpreted.< Less