Kategoria BISAC: Psychology >> Statistics

• Focuses on the ideas and practicalities of statistics in psychology, rather than an array of complex numbers and formulas
  
• Covers the key tests and concepts relevant to the undergraduate student
  
• Includes a...

This new edition of one of the most widely read textbooks in its field introduces the reader to data analysis with the most powerful and versatile statistical package on the market: IBM SPSS Statistics 19.

Each new release of SPSS Statistics features new options and other improvements. There remains a core of fundamental operating principles and techniques which have continued to apply to all releases issued in recent years and have been proved to be worth communicating in a small volume.

This practical and informal book combines simplicity and clarity of...

Statistics Explained is an accessible introduction to statistical concepts and ideas. It makes few assumptions about the reader s statistical knowledge, carefully explaining each step of the analysis and the logic behind it. The book:

• provides a clear explanation of statistical analysis and the key statistical tests employed in analysing research data
• gives accessible explanations of how and why statistical tests are used
• includes a wide range of practical, easy-to-understand worked examples.

This step-by-step guide is written for R and latent variable model (LVM) novices. Utilizing a path model approach and focusing on the lavaan package, this book is designed to help readers quickly understand LVMs and their analysis in R. The author reviews the reasoning behind the syntax selected and provides examples that demonstrate how to analyze data for a variety of LVMs.　 Featuring examples applicable to psychology, education, business, and other social and health sciences, minimal text is devoted to theoretical underpinnings. The material is presented...

Featuring in-depth coverage of categorical and nonparametric statistics, this book provides a conceptual framework for choosing the most appropriate type of test in various research scenarios. Class tested at the University of Nevada, the book's clear explanations of the underlying assumptions, computer simulations, and Exploring the Concept boxes help reduce reader anxiety. Problems inspired by actual studies provide meaningful illustrations of the techniques. The underlying assumptions of each test and the factors that impact validity and statistical power are reviewed so...

Designed to help readers analyze and interpret research data using IBM SPSS, this user-friendly book shows readers how to choose the appropriate statistic based on the design; perform intermediate statistics, including multivariate statistics; interpret output; and write about the results. The book reviews research designs and how to assess the accuracy and reliability of data; how to determine whether data meet the assumptions of statistical tests; how to calculate and interpret effect sizes for intermediate statistics, including odds ratios for logistic analysis; how to compute and...

Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis introduces latent variable models by utilizing path diagrams to explain the relationships in the models. This approach helps less mathematically-inclined readers to grasp the underlying relations among path analysis, factor analysis, and structural equation modeling, and to set up and carry out such analyses. This revised and expanded fifth edition again contains key chapters on path analysis, structural equation models, and exploratory factor analysis. In addition, it contains new material...

Latent Variable Models: An Introduction to Factor, Path, and Structural Equation Analysis introduces latent variable models by utilizing path diagrams to explain the relationships in the models. This approach helps less mathematically-inclined readers to grasp the underlying relations among path analysis, factor analysis, and structural equation modeling, and to set up and carry out such analyses. This revised and expanded fifth edition again contains key chapters on path analysis, structural equation models, and exploratory factor analysis. In addition, it contains new material...

Data Analysis: A Model Comparison Approach to Regression, ANOVA, and Beyond is an integrated treatment of data analysis for the social and behavioral sciences. It covers all of the statistical models normally used in such analyses, such as multiple regression and analysis of variance, but it does so in an integrated manner that relies on the comparison of models of data estimated under the rubric of the general linear model. 　

Data Analysis also describes how the model comparison approach and uniform framework can be applied to models that include product...