Paperback : £38.60
Statistical methods in modern research increasingly entail developing, estimating and testing models for data. Rather than rigid methods of data analysis, the need today is for more flexible methods for modelling data.
In this logical, easy-to-follow and exceptionally clear book, David Flora provides a comprehensive survey of the major statistical procedures currently used. His innovative model-based approach teaches you how to:
Statistical Methods for the Social and Behavioural Sciences: A Model Based Approach is the essential guide for those looking to extend their understanding of the principles of statistics, and begin using the right statistical modeling method for their own data. It is particularly suited to second or advanced courses in statistical methods across the social and behavioural sciences.
Show moreStatistical methods in modern research increasingly entail developing, estimating and testing models for data. Rather than rigid methods of data analysis, the need today is for more flexible methods for modelling data.
In this logical, easy-to-follow and exceptionally clear book, David Flora provides a comprehensive survey of the major statistical procedures currently used. His innovative model-based approach teaches you how to:
Statistical Methods for the Social and Behavioural Sciences: A Model Based Approach is the essential guide for those looking to extend their understanding of the principles of statistics, and begin using the right statistical modeling method for their own data. It is particularly suited to second or advanced courses in statistical methods across the social and behavioural sciences.
Show more1. Foundations of Statistical Modeling Demonstrated with Simple
Regression
2. Multiple Regression with Continuous Predictors
3. Regression with Categorical Predictors
4. Interactions in Multiple Regression: Models for Moderation
5. Using Multiple Regression to Model Mediation and Other Indirect
Effects
6. Introduction to Multilevel Modeling
7. Basic Matrix Algebra for Statistical Modeling
8. Exploratory Factor Analysis
9. Structural Equation Modeling I: Path Analysis
10. Structural Equation Modeling II: Latent Variable Models
11. Growth Curve Modeling
David B. Flora`s textbook, Statistical Methods for the Social and
Behavioural Sciences, is a welcome offering for instructors and
students alike. Not only is it well written and accessible, one of
its main strengths is its coverage of techniques. The book begins
with a substantial overview of multiple regression, including an up
to date presentation of moderation and mediation, and takes the
reader through a broad array of techniques, including Factor
Analysis, Multi-level Modeling, and Structural Equation Modeling.
The selection of content for this textbook is a strength!
*Dennis L Jackson*
In this exceptional textbook, David Flora has introduced an
innovative model-based approach to understanding and applying
statistical principles and techniques. This textbook helps students
and researchers to understand their data and choose the most
appropriate statistical models to fit to their data using any
software package. The excellent and easy-to-follow style engages
the reader and the use of clear illustrations and example data
analyses makes advanced statistical procedures accessible to
students and researchers.
*Jala Rizeq*
This book is so incredibly impressive. There are many general
statistics texts in the field, but this one is fundamentally
different by approaching the topic through a model-based
perspective. It reaches a broad audience on many levels -- it’s
clearly technically rigorous, but makes wonderful use of bold in
the text, call-out boxes, section recaps, and recommended readings.
The topical coverage is also great -- this could be used either as
a primary or secondary resource for a large variety of classes
ranging from general introductions to multivariate topics to a
graduate regression course.
*Patrick J. Curran*
The perfect companion guide to common statistical issues ranging
from simple regression to structural equation modeling that new
graduate students or seasoned faculty members will invariably
encounter on their research journeys. This text will be useful for
busy researchers throughout graduate school and tenure. Clear and
accessible with engaging, thoughtful examples and diagrams, this is
a welcome addition that will be my go-to text for guidance on
statistical models. I foresee this text being on my bookshelf for
years to come.
*Joshua Guilfoyle*
David Flora′s Statistical Methods for the Social and Behavioural
Sciences presents pertinent statistical topics with sufficient
depth of coverage for an introductory multivariate textbook, and
does so with an exceptional level of clarity. Interesting and
relevant examples are accompanied by code from key software
packages so that readers can further understand the concepts
described in each chapter. For these reasons, Statistical Methods
for the Social and Behavioural Sciences would serve as an excellent
textbook for a graduate level multivariate course.
*Alyssa Counsell*
Dave Flora’s textbook "Statistical Methods for the Social and
Behavioural Sciences" is an excellent resource for graduate
students, researchers, and professors alike who would like to
improve their knowledge in a wide range of statistical methods.
Each chapter provides the perfect balance of technical details to
practical applications that provides an excellent foundation of
knowledge without being overwhelming. Readers will find that this
textbook is designed to answer their questions before they realize
they have them and that it makes an invaluable addition to any
researcher’s bookshelf.
*Samantha Fashler*
This text by Dave Flora is an excellent resource for researchers.
Each chapter builds upon the next in a logical progression. The use
of examples throughout, particularly having datasets available
online so you can follow-along yourself, ensures understanding. The
structure of the individual chapters is so helpful, particularly
the chapter summaries and annotated selections for recommended
readings. It’s a text I can see myself referring to frequently in
the future.
*Caroline Barnes, PhD, R.Psych*
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