Statistics 31

Multilevel Modeling is a concise, practical guide to building models for multilevel and longitudinal data. Author Douglas A. Luke begins by providing a rationale for multilevel models; outlines the ……続きを見る

A Guide to R for Social and Behavioral Science Statistics is a short, accessible book for learning R. This handy guide contains basic information on statistics for undergraduates and graduate studen……続きを見る

Multilevel Modeling: Applications in STATA®, IBM® SPSS®, SAS®, R & HLM™ provides a gentle, hands-on illustration of the most common types of multilevel modeling software, offering instructors multip……続きを見る

This book introduces researchers and students to the concepts and generalized linear models for analyzing quantitative random variables that have one or more bounds. Examples of bounded variables in……続きを見る

Apply statistics to your everyday life. Statistics and Data Analysis for Social Science helps students to build a strong foundational understanding of statistics by providing clarity around when and……続きを見る

Spatial Regression Models for the Social Sciences shows researchers and students how to work with spatial data without the need for advanced mathematical statistics. Focusing on the methods that are……続きを見る

A firm knowledge of factor analysis is key to understanding much published research in the social and behavioral sciences. Exploratory Factor Analysis by W. Holmes Finch provides a solid foundation ……続きを見る

Do you want to learn R? This book is built on the premise that anyone with a bit of free time and a healthy curiosity can learn to use R in their studies or at work. The authors focus on using R to ……続きを見る

This Study Guide for introductory statistics courses in education departments is designed to accompany Neil J. Salkind and Bruce B. Frey’s best-selling Statistics for People Who (Think They) Hate St……続きを見る

Neil J. Salkind’s bestselling Statistics for People Who (Think They) Hate Statistics has been helping ease student anxiety around an often intimidating subject since it first published in 2000. Now ……続きを見る

Regression diagnostics are methods for determining whether a regression model that has been fit to data adequately represents the structure of the data. For example, if the model assumes a linear (s……続きを見る

An R Companion for Applied Statistics II: Multivariable and Multivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use R to ……続きを見る

Generalized Linear Models: A Unified Approach provides an introduction to and overview of GLMs, with each chapter carefully laying the groundwork for the next. The Second Edition provides examples u……続きを見る

Several decades of psychometric research have led to the development of sophisticated models for multidimensional test data, and in recent years, multidimensional item response theory (MIRT) has bec……続きを見る

The Fourth Edition of Statistics: A Gentle Introduction shows students that an introductory statistics class doesn’t need to be difficult or dull. This text minimizes students’ anxieties about math ……続きを見る

Gathering Social Network Data provides an important complement to existing books that focus on social network analysis, and offers more detailed coverage than is available in existing chapter-length……続きを見る

David Knoke and Song Yang′s Social Network Analysis, Third Edition provides a concise introduction to the concepts and tools of social network analysis. The authors convey key material while at the ……続きを見る

This Study Guide for introductory statistics courses in health and nursing departments is designed to accompany Salkind and Frey’s Statistics for People Who (Think They) Hate Statistics, Seventh Edi……続きを見る

Rebecca M. Warner’s bestselling Applied Statistics: From Bivariate Through Multivariate Techniques has been split into two volumes for ease of use over a two-course sequence. Applied Statistics II: ……続きを見る

This Student Study Guide includes chapter outlines, chapter summaries, learning objectives, key terms, true/false, short answer and essay questions. Exercises are also included for students to test ……続きを見る

Using Stata for Quantitative Analysis offers a brief but thorough introduction to analyzing data in undergraduate and graduate level research methods, statistics, and data analysis courses using Sta……続きを見る

This Study Guide for introductory statistics courses in psychology departments is designed to accompany Neil J. Salkind and Bruce B. Frey’s best-selling Statistics for People Who (Think They) Hate S……続きを見る

Multilevel Structural Equation Modeling serves as a minimally technical overview of multilevel structural equation modeling (MSEM) for applied researchers and advanced graduate students in the socia……続きを見る

An R Companion for Applied Statistics I: Basic Bivariate Techniques breaks the language of the R software down into manageable chunks in order to help students learn how to use it. R is a powerful, ……続きを見る

Spatial Regression Models illustrates the use of spatial analysis in the social sciences within a regression framework and is accessible to readers with no prior background in spatial analysis. The ……続きを見る

Introduction to Power Analysis: Two-Group Studies provides readers with the background, examples, and explanation they need to read technical papers and materials that include complex power analyses……続きを見る

What statistical test should I use for this kind of data? How do I set up the data? What parameters should I specify when ordering the test? How do I interpret the results? Herschel Knapp′s friendly……続きを見る

Now with a new companion website! Using IBM® SPSS® Statistics: An Interactive Hands-On Approach, Third Editiongives readers an accessible and comprehensive guide to walking through SPSS®, providing ……続きを見る

Fundamental Statistics for the Social and Behavioral Sciences, Second Edition, places statistics within the research process, illustrating how they are used to answer questions and test ideas. Stude……続きを見る

A Crash Course in Statistics is a short introduction to key statistical methods including descriptive statistics, one-way and two-way ANOVA, the t-test, and Chi Square. Each of the five chapters pro……続きを見る