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: Understand and choose the right statistical model to fit your data Match substantive theory and statistical models Apply statistical procedures hands-on, with example data analyses Develop and use graphs to understand data and fit models to data Work with statistical modeling principles using any software package Learn by applying, with input and output files for R, SAS, SPSS, and Mplus. 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.
Explore classic and cutting-edge statistical tools used in conducting diverse research in the behavioral and social sciences Inspired by the multifaceted Encyclopedia of Statistical Sciences, Second Edition, this book provides a concise, ...
This accessible guide covers basic to advanced concepts in a clear, concrete, and readable style. Essentials of Statistics for the Social and Behavioral Sciences guides you to a better understanding of basic concepts of statistical methods.
Features: Presents an in-depth description of both classic and modern methods Explains and illustrates why recent advances can provide more power and a deeper understanding of data Provides numerous illustrations using the software R ...
The book also examines advanced techniques for users of computer packages or data analysis, such as Minitab, SPSS, SAS, SuperANOVA, Statistica, BMPD, SYSTAT, Genstat, and GLIM.
Geared toward social and behavioural statistics students, especially those with no background in computer science, this handy guide contains basic information on statistics in the R language.
In this fully updated edition of Using Basic Statistics in the Behavioral and Social Sciences, Annabel Ness Evans presents introductory statistics in a practical, conceptual, and humorous way, reducing the anxiety that many students ...
Designed for a two-semester, introductory course for graduate students in the social sciences, this text illustrates how to use R to apply both standard and modern methods to correct known problems with classic techniques.
Designed for a two-semester, introductory course for graduate students in the social sciences, this text introduces three major advances in the field: Early studies seemed to suggest that normality can be assumed with relatively small ...
Written by an interdisciplinary team of global experts, this book is an invaluable tool for anyone learning about research methods.
Designed for a two-semester, introductory course for graduate students in the social sciences, this text illustrates how to use R to apply both standard and modern methods to correct known problems with classic techniques.