The aim of this book is to bridge the gap between introductory and more advanced ‘technical’ books on quantitative methods, helping the reader to progress clearly.

This introductory textbook provides an inexpensive, brief overview of statistics to help readers gain a better understanding of how statistics work and how to interpret them correctly. Each chapter describes a different statistical technique, ranging from basic concepts like central tendency and describing distributions to more advanced concepts such as t tests, regression, repeated measures ANOVA, and factor analysis. Each chapter begins with a short description of the statistic ...

This classic text on multiple regression is noted for its nonmathematical, applied, and data-analytic approach. Readers profit from its verbal-conceptual exposition and frequent use of examples.The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple...

This book develops an intuitive understanding of IRT principles through the use of graphical displays and analogies to familiar psychological principles. It surveys contemporary IRT models, estimation methods, and computer programs. Polytomous IRT models are given central coverage since many psychological tests use rating scales.Ideal for clinical, industrial, counseling, educational, and behavioral medicine professionals and students familiar with classical testing principles, exp...

Designing Experiments and Analyzing Data: A Model Comparison Perspective (3rd edition) offers an integrative conceptual framework for understanding experimental design and data analysis. Maxwell, Delaney, and Kelley first apply fundamental principles to simple experimental designs followed by an application of the same principles to more complicated designs. Their integrative conceptual framework better prepares readers to understand the logic behind a general strategy of data analysis tha...

While most books on missing data focus on applying sophisticated statistical techniques to deal with the problem after it has occurred, this volume provides a methodology for the control and prevention of missing data. In clear, nontechnical language, the authors help the reader understand the different types of missing data and their implications for the reliability, validity, and generalizability of a study’s conclusions. They provide practical recommendations for designing studies that ...

This latest edition has been fully updated to accommodate the needs of users of SPSS Releases 17, 18 and 19 while still being applicable to users of SPSS Releases 15 and 16.As with previous editions, Alan Bryman and Duncan Cramer continue to offer a comprehensive and user-friendly introduction to the widely used IBM SPSS Statistics. The simple, non-technical approach to quantitative data analysis enables the reader to quickly become familiar with SPSS and with the tests available t...

Research methods are such phenomena that every researcher wishes to learn. It has been observed that researchers find it difficult to conduct an in-depth analysis in their areas of specialization without a sound knowledge of the scientific process of conducting research. Researchers may consult many books and articles but their inherent inquisitiveness will remain unfulfilled if they lack patience in devoting time to understand research methods. They must remember that little knowledge is ...

Basic Statistics provides an accessible and comprehensive introduction to statistics using the free, state-of-the-art, powerful software program R. This book is designed to both introduce students to key concepts in statistics and to provide simple instructions for using R.This concise book:Teaches essential concepts in statistics, assuming little background knowledge on the part of the readerIntroduces students to R with as few sub-commands as possible for ease of useProvid...

`The authors make excellent use of illustrative examples′ - Reference ReviewsThe SAGE Dictionary of Statistics provides students and researchers with an accessible and definitive resource to use when studying statistics in the social sciences, reading research reports and undertaking data analysis. Written by leading academics in the field of methodology and statistics, the Dictionary will be an essential study guide for the first-time researcher a...

To say that complex data analyses are ubiquitous in the education and social sciences might be an understatement. Funding agencies and peer-review journals alike require that researchers use the most appropriate models and methods for explaining phenomena. Univariate and multivariate data structures often require the application of more rigorous methods than basic correlational or analysis of variance models. Additionally, though a vast set of resources may exist on how to run analysis, di...

This book takes a fresh look at applying regression analysis in the behavioural sciences by introducing the reader to regression analysis through a simple model-building approach.The authors start with the basics and begin by re-visiting the mean, and the standard deviation, with which most readers will already be familiar, and show that they can be thought of a least squares model. The book then shows that this least squares model is actually a special case of a regression analysi...