Data Sets To Accompany Basic Statistics For The Behavioral Sciences

A comprehensive and user-friendly introduction to statistics for behavioral science students revised and updated Refined over seven editions by master teachers, this book gives instructors and students alike clear examples and carefully crafted exercises to support the teaching and learning of statistics for both manipulating and consuming data. One of the most popular and respected statistics texts in the behavioral sciences, the Seventh Edition of Introductory Statistics for the Behavioral Sciences has been fully revised. The new edition presents all the topics students in the behavioral sciences need in a uniquely accessible and easy-to-understand format, aiding in the comprehension and implementation of the statistical analyses most commonly used in the behavioral sciences. The Seventh Edition features: A continuous narrative that clearly explains statistics while tracking a common data set throughout, making the concepts unintimidating and memorable, and providing a framework that connects all of the topics and allows for easy comparison of different statistical analyses Coverage of important aspects of research design throughout the text, such as the "correlation is not causality" principle Updated and annotated SPSS output at the end of each chapter with step-by-step instructions Updated examples and exercises An expanded website, at www.wiley.com/go/welkowitz, with test bank, chapter quizzes, and PowerPoint slides for instructors, as well as a second website for students with additional basic math coverage, math review exercises, a study guide, a set of additional SPSS exercises, and more downloadable data sets

Nolan and Heinzen’s engaging introduction to statistics has captivated students with its easy readability and vivid examples drawn from everyday life. The mathematics of statistical reasoning are made accessible with careful explanations and a helpful three-tier approach to working through exercises: Clarifying the Concepts, Calculating the Statistics, and Applying the Concepts. New pedagogy, end-of-chapter material, and the groundbreaking learning space StatsPortal give students even more tools to help them master statistics than ever before.

An introductory applied statistics text that can be used at either undergraduate or graduate level.

Workbook for Introductory Statistics for the Behavioral Sciences, Second Edition provides an introduction to the concepts of statistics. This book aims to help students obtain the necessary practice in a first course in statistics, which is essential to learning and understanding the material. This edition begins with an overview of summation notation exercises with additional computational practices. This text then provides computational exercises for regular frequency distributions, grouped frequency distributions, cumulative frequency distribution, graphic representations, measures of central tendency, measures of variability, and general transformations. This book discusses as well the probability and the general strategy of inferential statistics as well as the differences between the means of two populations. The reader is also introduced to the main advantage of nonparametric and distribution-free statistical tests in which they do not require the population being sampled to the normally distributed. This book is a valuable resource for students of behavioral and social sciences.

This manual for the statistical packages SG & SPSS accompanies 'Statistics for the Behavioral Sciences'

Multivariate Analysis for the Behavioral Sciences, Second Edition is designed to show how a variety of statistical methods can be used to analyse data collected by psychologists and other behavioral scientists. Assuming some familiarity with introductory statistics, the book begins by briefly describing a variety of study designs used in the behavioral sciences, and the concept of models for data analysis. The contentious issues of p-values and confidence intervals are also discussed in the introductory chapter. After describing graphical methods, the book covers regression methods, including simple linear regression, multiple regression, locally weighted regression, generalized linear models, logistic regression, and survival analysis. There are further chapters covering longitudinal data and missing values, before the last seven chapters deal with multivariate analysis, including principal components analysis, factor analysis, multidimensional scaling, correspondence analysis, and cluster analysis. Features: Presents an accessible introduction to multivariate analysis for behavioral scientists Contains a large number of real data sets, including cognitive behavioral therapy, crime rates, and drug usage Includes nearly 100 exercises for course use or self-study Supplemented by a GitHub repository with all datasets and R code for the examples and exercises Theoretical details are separated from the main body of the text Suitable for anyone working in the behavioral sciences with a basic grasp of statistics