Monday, October 31, 2011

SPSS Survival Manual (Spiral-bound)

SPSS Survival Manual
SPSS Survival Manual (Spiral-bound)
By Julie Pallant

Review & Description

A lifeline to students and researchers grappling with SPSS data analysis software

This fully revised and updated edition of the SPSS Survival Manual guides readers through the entire research process, helping them choose the right data analysis technique for any project. From the formulation of research questions, to the design of the study and analysis of data, to reporting the results, the author discusses basic and advanced statistical techniques. Each technique is clearly outlined, with step-by-step procedures for performing the analysis, a detailed guide to interpreting SPSS output, and an example of how to present the results in a report. Statistical techniques covered include:

  • Descriptive statistics
  • Correlation
  • Multiple regression
  • Logistic regression
  • Factor analysis
  • T-tests
  • Analysis of variance
  • Multivariate analysis of variance
  • Analysis of covariance
  • Non-parametric tests

Illustrated with screen grabs, examples of output, and tips, the SPSS Survival Manual can be used by researchers at any level across all disciplines. It is supported by a website with sample data and guidelines on report writing and is fully updated for SPSS Version 12.

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Parallel R (Paperback)

Parallel R
Parallel R (Paperback)
By Q. Ethan McCallum

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Customer tags: r, statistics

Review & Description

R is a wonderful thing, indeed: in recent years this free, open-source product has become a popular toolkit for statistical analysis and programming. Two of R's limitations -- that it is single-threaded and memory-bound -- become especially troublesome in the current era of large-scale data analysis. It's possible to break past these boundaries by putting R on the parallel path. Parallel R will describe how to give R parallel muscle. Coverage will include stalwarts such as snow and multicore, and also newer techniques such as Hadoop and Amazon's cloud computing platform.

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Sunday, October 30, 2011

Introduction to Mixed Modelling: Beyond Regression and Analysis of Variance (Hardcover)

Introduction to Mixed Modelling: Beyond Regression and Analysis of Variance
Introduction to Mixed Modelling: Beyond Regression and Analysis of Variance (Hardcover)
By Nick Galwey

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Review & Description

Mixed modelling is one of the most promising and exciting areas of statistical analysis, enabling more powerful interpretation of data through the recognition of random effects. However, many perceive mixed modelling as an intimidating and specialized technique. This book introduces mixed modelling analysis in a simple and straightforward way, allowing the reader to apply the technique confidently in a wide range of situations.

Introduction to Mixed Modelling shows that mixed modelling is a natural extension of the more familiar statistical methods of regression analysis and analysis of variance. In doing so, it provides the ideal introduction to this important statistical technique for those engaged in the statistical analysis of data.

This essential book:

  • Demonstrates the power of mixed modelling in a wide range of disciplines, including industrial research, social sciences, genetics, clinical research, ecology and agricultural research.
  • Illustrates how the capabilities of regression analysis can be combined with those of ANOVA by the specification of a mixed model.
  • Introduces the criterion of Restricted Maximum Likelihood (REML) for the fitting of a mixed model to data.
  • Presents the application of mixed model analysis to a wide range of situations and explains how to obtain and interpret Best Linear Unbiased Predictors (BLUPs).
  • Features a supplementary website containing solutions to exercises, further examples, and links to the computer software systems GenStat and R.

This book provides a comprehensive introduction to mixed modelling, ideal for final year undergraduate students, postgraduate students and professional researchers alike. Readers will come from a wide range of scientific disciplines including statistics, biology, bioinformatics, medicine, agriculture, engineering, economics, and social sciences. Read more


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Saturday, October 29, 2011

A Gentle Introduction to Stata, Third Edition (Paperback)

A Gentle Introduction to Stata, Third Edition
A Gentle Introduction to Stata, Third Edition (Paperback)
By Alan C. Acock

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Review & Description

Updated to reflect the new features of Stata 11, A Gentle Introduction to Stata, Third Edition continues to help new Stata users become proficient in Stata. After reading this introductory text, you will be able to enter, build, and manage a data set as well as perform fundamental statistical analyses.

New to the Third Edition

  • A new chapter on the analysis of missing data and the use of multiple-imputation methods
  • Extensive revision of the chapter on ANOVA
  • Additional material on the application of power analysis

The book covers data management; good work habits, including the use of basic do-files; basic exploratory statistics, including graphical displays; and analyses using the standard array of basic statistical tools, such as correlation, linear and logistic regression, and parametric and nonparametric tests of location and dispersion. Rather than splitting these topics by their Stata implementation, the material on graphics and postestimation are woven into the text in a natural fashion. The author teaches Stata commands by using the menus and dialog boxes while still stressing the value of do-files. Each chapter includes exercises and real data sets are used throughout.

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An Introduction to Stata for Health Researchers, Third Edition (Paperback)

An Introduction to Stata for Health Researchers, Third Edition
An Introduction to Stata for Health Researchers, Third Edition (Paperback)
By Svend Juul

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Review & Description

An Introduction to Stata for Health Researchers, Third Edition systematically covers data management, simple description and analysis, and more advanced analyses that are most often used in health research, such as regression models, survival analysis, measurement, and diagnosis. It also describes many graph types as well as how to modify the appearance of a graph.

Throughout the text, the authors emphasize the importance of good documentation habits to prevent errors and wasted time. They demonstrate the use of strategies and tools for documentation. Robust data sets can be downloaded from the book’s website.

What’s New
This third edition presents some of the new features in Stata 11, including the new, flexible syntax for factor variables. It also incorporates Stata 11 in the rewritten chapters on regression and survival analysis. Taking into account the improved availability of online documentation, this edition points to further reading in the online manuals.

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Wednesday, October 26, 2011

What is a p-value anyway? 34 Stories to Help You Actually Understand Statistics (Paperback)

What is a p-value anyway? 34 Stories to Help You Actually Understand Statistics
What is a p-value anyway? 34 Stories to Help You Actually Understand Statistics (Paperback)
By Andrew Vickers

Review & Description

What is a p-value Anyway? offers a fun introduction to the fundamental principles of statistics, presenting the essential concepts in thirty-four brief, enjoyable stories. Drawing on his experience as a medical researcher, Vickers blends insightful explanations and humor, with minimal math, to help readers understand and interpret the statistics they read every day.

 

Describing data; Data distributions; Variation of study results: confidence intervals; Hypothesis testing; Regression and decision making; Some common statistical errors, and what they teach us

 

For all readers interested in statistics. Read more


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Monday, October 24, 2011

Sequential Analysis and Observational Methods for the Behavioral Sciences (Paperback)

Sequential Analysis and Observational Methods for the Behavioral Sciences
Sequential Analysis and Observational Methods for the Behavioral Sciences (Paperback)
By Roger Bakeman

Review & Description

Behavioral scientists - including those in psychology, infant and child development, education, animal behavior, marketing, and usability studies - use many methods to measure behavior. Systematic observation is used to study relatively natural, spontaneous behavior as it unfolds sequentially in time. This book emphasizes digital means to record and code such behavior; while observational methods do not require them, they work better with them. Key topics include devising coding schemes, training observers, and assessing reliability, as well as recording, representing, and analyzing observational data. In clear and straightforward language, this book provides a thorough grounding in observational methods along with considerable practical advice. It describes standard conventions for sequential data and details how to perform sequential analysis with a computer program developed by the authors. The book is rich with examples of coding schemes and different approaches to sequential analysis, including both statistical and graphical means. Read more


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Wednesday, October 19, 2011

Even You Can Learn Statistics: A Guide for Everyone Who Has Ever Been Afraid of Statistics (2nd Edition) (Kindle Edition)

Even You Can Learn Statistics: A Guide for Everyone Who Has Ever Been Afraid of Statistics (2nd Edition)
Even You Can Learn Statistics: A Guide for Everyone Who Has Ever Been Afraid of Statistics (2nd Edition) (Kindle Edition)
By David M. Levine

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Review & Description

The Completely Updated Guide for Everyone Who’s Ever Been Afraid of Statistics!

The easy, practical, up-to-date introduction to statistics–for everyone! Thought you couldn’t learn statistics? You can–and you will! One easy step at a time, this fully updated book teaches you all the statistical techniques you’ll need for finance, quality, marketing, the social sciences, or anything else! Simple jargon-free explanations help you understand every technique. Practical examples and worked-out problems give you hands-on practice. Special sections present detailed instructions for developing statistical answers, using spreadsheet programs or any TI-83/TI-84 compatible calculator. This edition delivers new examples, more detailed problems and sample solutions, plus an all-new chapter on powerful multiple regression techniques. Hate math? No sweat. You’ll be amazed at how little you need. Like math? Optional “Equation Blackboard” sections reveal the mathematical foundations of statistics right before your eyes!

 

Here’s Just Some of What You’ll Learn How to Do...

• Construct and interpret statistical charts and tables with Excel or OpenOffice.org Calc 3

• Work with mean, median, mode, standard deviation, Z scores, skewness, and other descriptive statistics

• Use probability and probability distributions

• Work with sampling distributions and confidence intervals

• Test hypotheses with Z, t, chi-square, ANOVA, and other techniques

• Perform powerful regression analysis and modeling

• Use multiple regression to develop models that contain several independent variables

• Master specific statistical techniques for quality and Six Sigma programs

 

About the Web Site

Download practice files, templates, data sets, and sample spreadsheet models–including ready-to-use solutions for your own work! www.ftpress.com/youcanlearnstatistics2e

The Completely Updated Guide for Everyone Who’s Ever Been Afraid of Statistics!

The easy, practical, up-to-date introduction to statistics–for everyone! Thought you couldn’t learn statistics? You can–and you will! One easy step at a time, this fully updated book teaches you all the statistical techniques you’ll need for finance, quality, marketing, the social sciences, or anything else! Simple jargon-free explanations help you understand every technique. Practical examples and worked-out problems give you hands-on practice. Special sections present detailed instructions for developing statistical answers, using spreadsheet programs or any TI-83/TI-84 compatible calculator. This edition delivers new examples, more detailed problems and sample solutions, plus an all-new chapter on powerful multiple regression techniques. Hate math? No sweat. You’ll be amazed at how little you need. Like math? Optional “Equation Blackboard” sections reveal the mathematical foundations of statistics right before your eyes!

 

Here’s Just Some of What You’ll Learn How to Do...

• Construct and interpret statistical charts and tables with Excel or OpenOffice.org Calc 3

• Work with mean, median, mode, standard deviation, Z scores, skewness, and other descriptive statistics

• Use probability and probability distributions

• Work with sampling distributions and confidence intervals

• Test hypotheses with Z, t, chi-square, ANOVA, and other techniques

• Perform powerful regression analysis and modeling

• Use multiple regression to develop models that contain several independent variables

• Master specific statistical techniques for quality and Six Sigma programs

 

About the Web Site

Download practice files, templates, data sets, and sample spreadsheet models–including ready-to-use solutions for your own work! www.ftpress.com/youcanlearnstatistics2e

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Multiple Regression in Practice (Quantitative Applications in the Social Sciences) (Paperback)

Multiple Regression in Practice (Quantitative Applications in the Social Sciences)
Multiple Regression in Practice (Quantitative Applications in the Social Sciences) (Paperback)
By William Dale Berry

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Review & Description

Berry and Feldman provide a systematic treatment of many of the major problems encountered in using regression analysis. The authors discuss: the consequences of violating the assumptions of the regression model; procedures for detecting when such violations occur; and strategies for dealing with these problems when they arise. The monograph was written without the use of matrix algebra, and numerous examples are provided from political science, sociology, and economics.

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Tuesday, October 18, 2011

Regression with Dummy Variables (Quantitative Applications in the Social Sciences) (Paperback)

Regression with Dummy Variables (Quantitative Applications in the Social Sciences)
Regression with Dummy Variables (Quantitative Applications in the Social Sciences) (Paperback)
By Melissa A. Hardy

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Review & Description

It is often necessary for social scientists to study differences in groups, such as gender or race differences in attitudes, buying behavior, or socioeconomic characteristics. When the researcher seeks to estimate group differences through the use of independent variables that are qualitative, dummy variables allow the researcher to represent information about group membership in quantitative terms without imposing unrealistic measurement assumptions on the categorical variables. Beginning with the simplest model, Hardy probes the use of dummy variable regression in increasingly complex specifications, exploring issues such as: interaction, heteroscedasticity, multiple comparisons and significance testing, the use of effects or contrast coding, testing for curvilinearity, and estimating a piecewise linear regression.

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Monday, October 17, 2011

A Passion for Facts: Social Surveys and the Construction of the Chinese Nation-State, 1900-1949 (Asia Pacific Modern) (Hardcover)

A Passion for Facts: Social Surveys and the Construction of the Chinese Nation-State, 1900-1949 (Asia Pacific Modern)
A Passion for Facts: Social Surveys and the Construction of the Chinese Nation-State, 1900-1949 (Asia Pacific Modern) (Hardcover)
By Tong Lam

Review & Description

In this path-breaking book, Tong Lam examines the emergence of the "culture of fact" in modern China, showing how elites and intellectuals sought to transform the dynastic empire into a nation-state, thereby ensuring its survival. Lam argues that an epistemological break away from traditional modes of understanding the observable world began around the turn of the twentieth century. Tracing the Neo-Confucian school of evidentiary research and the modern departure from it, Lam shows how, through the rise of the social survey, "the fact" became a basic conceptual medium and source of truth. In focusing on China's social survey movement, A Passion for Facts analyzes how information generated by a range of research practices--census, sociological investigation, and ethnography--was mobilized by competing political factions to imagine, manage, and remake the nation. Read more


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Sunday, October 16, 2011

Encyclopedia of Baseball Statistics: From A to ZR (Paperback)

Encyclopedia of Baseball Statistics: From A to ZR
Encyclopedia of Baseball Statistics: From A to ZR (Paperback)
By Eric Blabac

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Review & Description

The modern game of baseball is a stark contrast to the game of the past and statistics have continued to move to the forefront of the game. Watching a game on TV or listening to it on the radio, one is constantly bombarded with numbers of all kinds - how can one make sense of it all? Numbers constantly fly across your screen during each game and even the more mature fans may not truly understand what they mean. As one can imagine, the diversity of baseball statistics, the methods that create them and the fans who follow them is immense. This book makes no attempt to develop the next 'super stat' or tell you why Babe Ruth is better than Barry Bonds (or visa-versa). It merely attempts to not only present all well-known baseball statistics, but to present it in a way as to help the reader truly understand what the statistic really means and how that statistic can be used. If you have ever flipped through the many books or encyclopedias on baseball statistics one will quickly come to a conclusion - any real explanation of these statistics are placed in the very back of the book (usually in very tiny text) and typically with no real discussion on their calculation, context, or application. This text attempts to not only standardize baseball statistics as a subject, but to allow anyone to understand these statistics as well calculate them - no PhD required (but I suppose it helps). Read more


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Saturday, October 15, 2011

Introduction to Econometrics, Brief Edition (Paperback)

Introduction to Econometrics, Brief Edition
Introduction to Econometrics, Brief Edition (Paperback)
By James H. Stock

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Review & Description

In keeping with their successful introductory econometrics text, Stock and Watson motivate each methodological topic with a real-world policy application that uses data, so that readers apply the theory immediately. Introduction to Econometrics, Brief, is a streamlined version of their text, including the fundamental topics, an early review of statistics and probability, the core material of regression with cross-sectional data, and a capstone chapter on conducting empirical analysis.

Introduction and Review: Economic Questions and Data; Review of Probability; Review of Statistics. Fundamentals of Regression Analysis: Linear Regression with One Regressor; Regression with a Single Regressor: Hypothesis Tests and Confidence Intervals in the Single-Regressor Model; Linear Regression with Multiple Regressors; Hypothesis Tests and Confidence Intervals in the Multiple Regressor Model; Nonlinear Regression Functions; Assessing Studies Based on Multiple Regression; Conducting a Regression Study Using Economic Data.

MARKET: For all readers interested in econometrics.

 

 

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Econometrics (Hardcover)

Econometrics
Econometrics (Hardcover)
By Fumio Hayashi

Review & Description

Hayashi's Econometrics promises to be the next great synthesis of modern econometrics. It introduces first year Ph.D. students to standard graduate econometrics material from a modern perspective. It covers all the standard material necessary for understanding the principal techniques of econometrics from ordinary least squares through cointegration. The book is also distinctive in developing both time-series and cross-section analysis fully, giving the reader a unified framework for understanding and integrating results.

Econometrics has many useful features and covers all the important topics in econometrics in a succinct manner. All the estimation techniques that could possibly be taught in a first-year graduate course, except maximum likelihood, are treated as special cases of GMM (generalized methods of moments). Maximum likelihood estimators for a variety of models (such as probit and tobit) are collected in a separate chapter. This arrangement enables students to learn various estimation techniques in an efficient manner. Eight of the ten chapters include a serious empirical application drawn from labor economics, industrial organization, domestic and international finance, and macroeconomics. These empirical exercises at the end of each chapter provide students a hands-on experience applying the techniques covered in the chapter. The exposition is rigorous yet accessible to students who have a working knowledge of very basic linear algebra and probability theory. All the results are stated as propositions, so that students can see the points of the discussion and also the conditions under which those results hold. Most propositions are proved in the text.

For those who intend to write a thesis on applied topics, the empirical applications of the book are a good way to learn how to conduct empirical research. For the theoretically inclined, the no-compromise treatment of the basic techniques is a good preparation for more advanced theory courses.

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Multilevel Modeling (Quantitative Applications in the Social Sciences) (Paperback)

Multilevel Modeling (Quantitative Applications in the Social Sciences)
Multilevel Modeling (Quantitative Applications in the Social Sciences) (Paperback)
By Douglas A. Luke

Review & Description

Taking a practical, hands-on approach to multilevel modeling, this book provides readers with an accessible and concise introduction to HLM and how to use the technique to build models for hierarchical and longitudinal data. Each section of the book answers a basic question about multilevel modeling, such as, "How do you determine how well the model fits the data?" After reading this book, readers will understand research design issues associated with multilevel models, be able to accurately interpret the results of multilevel analyses, and build simple cross-sectional and longitudinal multilevel models. Read more


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Friday, October 14, 2011

Essentials of Econometrics + Data CD (Hardcover)

Essentials of Econometrics + Data CD
Essentials of Econometrics + Data CD (Hardcover)
By Damodar N. Gujarati

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This text provides a simple and straightforward introduction to econometrics for the beginner. The author's intent is to provide the student with a "user friendly," non-intimidating introduction to econometric theory and techniques. The book motivates students to understand econometric techniques through extensive examples, careful explanations, and a wide variety of problem material. The audience is undergraduate economics, agricultural economics, and business administration majors, MBA students and others in the social and behavioral sciences where econometric techniques, especially the techniques of linear regression analysis, are used. Read more


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Thursday, October 13, 2011

Applied Regression: An Introduction (Quantitative Applications in the Social Sciences) (Paperback)

Applied Regression: An Introduction (Quantitative Applications in the Social Sciences)
Applied Regression: An Introduction (Quantitative Applications in the Social Sciences) (Paperback)
By Michael S. Lewis-Beck

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Applied regression allows social scientists who are not specialists in quantitative techniques to arrive at clear verbal explanations of their numerical results. Provides a lucid discussion of more specialized subjects: analysis of residuals, interaction effects, specification error, multicollinearity, standardized coefficients, and dummy variables. Read more


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Friday, October 7, 2011

Econometric Analysis of Cross Section and Panel Data (Hardcover)

Econometric Analysis of Cross Section and Panel Data
Econometric Analysis of Cross Section and Panel Data (Hardcover)
By Jeffrey M. Wooldridge

Review & Description

This graduate text provides an intuitive but rigorous treatment of contemporary methods used in microeconometric research. The book makes clear that applied microeconometrics is about the estimation of marginal and treatment effects, and that parametric estimation is simply a means to this end. It also clarifies the distinction between causality and statistical association.

The book focuses specifically on cross section and panel data methods. Population assumptions are stated separately from sampling assumptions, leading to simple statements as well as to important insights. The unified approach to linear and nonlinear models and to cross section and panel data enables straightforward coverage of more advanced methods. The numerous end-of-chapter problems are an important component of the book. Some problems contain important points not fully described in the text, and others cover new ideas that can be analyzed using tools presented in the current and previous chapters. Several problems require the use of the data sets located at the author's website. Read more


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Statistics for Social Data Analysis (Hardcover)

Statistics for Social Data Analysis
Statistics for Social Data Analysis (Hardcover)
By David Knoke

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The fourth edition of STATISTICS FOR SOCIAL DATA ANALYSIS continues to show students how to apply statistical methods to answer research questions in various fields. Throughout the text, the authors underscore the importance of formulating substantive hypotheses before attempting to analyze quantitative data. An important aspect of this text is its realistic, hands-on approach. Actual datasets are used in most examples, helping students understand and appreciate what goes into the research process. The book focuses on the continuous-discrete distinction in considering the level at which a variable is measured. Rather than dwelling on the four conventional levels-of-measurement distinctions, the authors discuss statistics for analyzing continuous and discrete variables separately and in combination. Read more


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Elements of Econometrics: Second Edition (Hardcover)

Elements of Econometrics: Second Edition
Elements of Econometrics: Second Edition (Hardcover)
By Jan Kmenta

Review & Description

This classic text has proven its worth in university classrooms and as a tool kit in research--selling over 40,000 copies in the United States and abroad in its first edition alone. Users have included undergraduate and graduate students of economics and business, and students and researchers in political science, sociology, and other fields where regression models and their extensions are relevant. The book has also served as a handy reference in the "real world" for people who need a clear and accurate explanation of techniques that are used in empirical research.
Throughout the book the emphasis is on simplification whenever possible, assuming the readers know college algebra and basic calculus. Jan Kmenta explains all methods within the simplest framework, and generalizations are presented as logical extensions of simple cases. And while a relatively high degree of rigor is preserved, every conflict between rigor and clarity is resolved in favor of the latter. Apart from its clear exposition, the book's strength lies in emphasizing the basic ideas rather than just presenting formulas to learn and rules to apply.
The book consists of two parts, which could be considered jointly or separately. Part one covers the basic elements of the theory of statistics and provides readers with a good understanding of the process of scientific generalization from incomplete information. Part two contains a thorough exposition of all basic econometric methods and includes some of the more recent developments in several areas.
As a textbook, Elements of Econometrics is intended for upper-level undergraduate and master's degree courses and may usefully serve as a supplement for traditional Ph.D. courses in econometrics. Researchers in the social sciences will find it an invaluable reference tool.
A solutions manual is also available for teachers who adopt the text for coursework.
Jan Kmenta is Professor Emeritus of Economics and Statistics, University of Michigan.
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Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling (Paperback)

Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling
Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling (Paperback)
By T. A. B. Snijders

Review & Description

The main methods, techniques and issues for carrying out multilevel modeling and analysis are covered in this book. The book is an applied introduction to the topic, providing a clear conceptual understanding of the issues involved in multilevel analysis and will be a useful reference tool. Information on designing multilevel studies, sampling, testing and model specification and interpretation of models is provided. A comprehensive guide to the software available is included. Multilevel Analysis is the ideal guide for researchers and applied statisticians in the social sciences, including education, but will also interest researchers in economics, and biological, medical and health disciplines. Read more


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Thursday, October 6, 2011

Hierarchical Linear Models: Applications and Data Analysis Methods (Advanced Quantitative Techniques in the Social Sciences) (Hardcover)

Hierarchical Linear Models: Applications and Data Analysis Methods (Advanced Quantitative Techniques in the Social Sciences)
Hierarchical Linear Models: Applications and Data Analysis Methods (Advanced Quantitative Techniques in the Social Sciences) (Hardcover)
By Anthony S. Bryk

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Popular in the First Edition for its rich, illustrative examples and lucid explanations of the theory and use of hierarchical linear models (HLM), the book has been reorganized into four parts with four completely new chapters. The first two parts, Part I on "The Logic of Hierarchical Linear Modeling" and Part II on "Basic Applications" closely parallel the first nine chapters of the previous edition with significant expansions and technical clarifications, such as:

* An intuitive introductory summary of the basic procedures for estimation and inference used with HLM models that only requires a minimal level of mathematical sophistication in Chapter 3
* New section on multivariate growth models in Chapter 6
* A discussion of research synthesis or meta-analysis applications in Chapter 7
* Data analytic advice on centering of level-1 predictors and new material on plausible value intervals and robust standard estimators

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100 Statistical Tests (Paperback)

100 Statistical Tests
100 Statistical Tests (Paperback)
By Gopal K. Kanji

Review & Description

This expanded and updated Third Edition of Gopal Kanji's best-selling resource on statistical tests covers all the most commonly used tests with information on how to calculate and interpret results with simple datasets. Each entry begins with a short summary statement about the test's purpose, and contains details of the test objective, the limitations (or assumptions) involved, a brief outline of the method, a worked example and the numerical calculation. This new edition also includes: " A brand new introduction to statistical testing with information to guide the reader through the book so that even non-statistics students can find information quickly and easily " Real-world explanations of how and when to use each test with examples drawn from wide range of disciplines. " A useful Classification of Tests table " All the relevant statistical tables for checking critical values 100 Statistical Tests: Third Edition is the one indispensable guide for users of statistical materials and consumers of statistical information at all levels and across all disciplines. Read more


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Survey Sampling (Wiley Classics Library) (Paperback)

Survey Sampling (Wiley Classics Library)
Survey Sampling (Wiley Classics Library) (Paperback)
By Leslie Kish

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An accessible book on sampling techniques with emphasis on and illustrations from surveys of human populations. Explains how to design and execute valid samples of moderate dimensions and difficulty, avoid selection biases and how to become more adept at evaluating sample results, judge their validity and limits of inference, applicability and precision. Contains numerous practical procedures, the domestic arts of sampling along with its science plus invaluable tricks that are usually learned only in apprenticeship. Read more


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Wednesday, October 5, 2011

Applied Logistic Regression Analysis (Quantitative Applications in the Social Sciences) (v. 106) (Paperback)

Applied Logistic Regression Analysis (Quantitative Applications in the Social Sciences) (v. 106)
Applied Logistic Regression Analysis (Quantitative Applications in the Social Sciences) (v. 106) (Paperback)
By Scott W. Menard

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The focus in this Second Edition is again on logistic regression models for individual level data, but aggregate or grouped data are also considered. The book includes detailed discussions of goodness of fit, indices of predictive efficiency, and standardized logistic regression coefficients, and examples using SAS and SPSS are included.

  • More detailed consideration of grouped as opposed to case-wise data throughout the book
  • Updated discussion of the properties and appropriate use of goodness of fit measures, R-square analogues, and indices of predictive efficiency
  • Discussion of the misuse of odds ratios to represent risk ratios, and of over-dispersion and under-dispersion for grouped data

Updated coverage of unordered and ordered polytomous logistic regression models. 

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Statistics for People Who (Think They) Hate Statistics: Excel 2007 Edition (Paperback)

Statistics for People Who (Think They) Hate Statistics: Excel 2007 Edition
Statistics for People Who (Think They) Hate Statistics: Excel 2007 Edition (Paperback)
By Neil J. Salkind

Review & Description

CourseSmart

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Utilizing the personable and clear approach that made Statistics for People Who (Think They) Hate Statistics a bestseller, Neil J. Salkind focuses on the use of Excel as the primary analytic tool in the Second Edition of Statistics for People Who Think They Hate Statistics – Excel 2007 Edition. Salkind walks readers through various statistical procedures, beginning with correlations and graphical representation of data and ending with inferential techniques and analysis of variance. Throughout the book, he reveals the full capabilities of Excel, beginning with Part I, which is an introduction to Excel to the end, where he presents an extensive overview of Excel functionality.

Key Features of the Second Edition:

  • Reflects all Excel material based on Excel 2007 including all screen grabs
  • Moves the reliability and validity chapter forward
  • Offers more examples throughout the text and more end of chapter exercises
  • Includes new and updated icons to explore certain topics in detail
  • Presents the answers to the Time to Practice exercises to follow in chapter rather than at end of book 
  • Contains an Appendix detailing the differences between Excel 2003 to Excel 2007
  • Incorporates the use of the new Data Analysis Toolpak option
  • Covers formulas and functions in more detail

Robust Ancillaries

The password-protected Instructor Resources Site at www.sagepub.com/salkind2einstr includes:

  • Chapter Overviews
  • PowerPoint presentations
  • Data sets
  • Questions and activities
  • Test questions with answers
  • SAGE journal articles & Web resources
  • Sample Syllabi

The student study site at http://www.sagepub.com/salkind2study contains   

  • Data sets for Excel 97-2003
  • Data sets for Excel 2007
  • Time for Practice data sets
  • Journal articles
  • Chapter overview/objectives
  • Questions and activities
  • Web resources

Intended Audience

This text is designed for students taking Introduction to Statistics courses in applied disciplines, especially in business & management and the human services.

Praise for Neil Salkind and Statistics for People Who (Think They) Hate Statistics

“Salkind’s book is in a class by itself. It is easily the best book of its kind that I have come across. I enthusiastically recommend it for anyone interested in the subject, and even (and especially) for those who aren’t!” -Russ Shafer-Landau, Professor, University of Wisconsin

“Your book Statistics for People Who (Think They) Hate Statistics has cleared up confusion and partial understandings that I have had for years. It is a must for anyone beginning or continuing their journey in this science. I love it, and will use it for all of the foreseeable future.” -Ronald A. Straube, Performance Improvement Coordinator, Mission Regional Medical Center

“Salkind’s examples assist with the application of key concepts and tests. The book is easy to read due to the way information is presented-such as the Tech Talk, Things to Remember, the Key to Difficulty Index, the various 10 lists, the icons, and the illustrations-including the cartoons. Even the title brings laughter to students-and humor can be a great antidote to stress!” -Mary Beth Zeni, Assistant Professor, Florida State School of Nursing

“I am a doctoral student and we simply love your book.” -Marisol Miller, PhD candidate, Arizona State University

“I just wanted to thank you for writing such a great book and for allowing people like me who are flung in at the deep end to stand a chance of understanding the basics and allowing us to get over the great fear of statistics! Thanks very much.” -Joanna Paolinelli, MS Student in Developmental Psychology

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Introducing Multilevel Modeling (Introducing Statistical Methods series) (Hardcover)

Introducing Multilevel Modeling (Introducing Statistical Methods series)
Introducing Multilevel Modeling (Introducing Statistical Methods series) (Hardcover)
By Ita G. G. Kreft

Buy new: $121.01
18 used and new from $89.00
Customer Rating: 4.0

First tagged by not a natural "Bob Bickel"
Customer tags: multilevel analysis, statistics

Review & Description

This is the first accessible and practical guide to using multilevel models in social research.

Multilevel approaches are becoming increasingly important in social, behavioural, and educational research and it is clear from recent developments that such models are seen as being more realistic, and potentially more revealing, than ordinary regression models.

While other books describe these multilevel models in considerable detail none focuses on the practical issues and potential problems of doing multilevel analyses that are covered in Introducing Multilevel Modeling.

The authors' approach is user-oriented and the formal mathematics and statistics are kept to a minimum. Other key fe Read more


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