An Introduction to Statistical Concepts, Second Edition
Lawrence Erlbaum Associates Inc (Publisher)
Published on 1. July 2000
Book
Hardback
536 pages
978-0-8058-2749-1 (ISBN)
Article exhausted; check for reprint
Description
This book provides comprehensive coverage so that it can be used in a single- or two-course sequence in statistics. It provides greater flexibility because it contains many topics not dealt with in other introductory texts. Its conceptual, intuitive approach allows for concepts to be easily stated and related to real-life examples. Throughout the text the author demonstrates how many statistical concepts can be related to one another. Unlike other texts, this book includes the following topics:
* skewness and kurtosis measures;
* inferences about two dependent proportions and two independent means with unequal variances;
* homogeneity of variance tests;
* layout of the data in ANOVA models;
* the ANOVA linear model;
* a wide variety of multiple comparison procedures;
* significance tests in multiple linear regression; and
* extensive discussion of assumptions and how to deal with assumption violations.
Numerous tables and figures help illustrate concepts and present examples within the text. An extensive bibliography is included. A number of pedagogical devices are included to increase the reader's conceptual understanding of statistics: chapter outlines; list of key concepts for each chapter; chapter objectives; numerous realistic examples; summary tables of statistical assumptions; extensive references; and end of chapter conceptual and computational problems.
An instructor's manual is available containing answers to all of the problems, as well as a collection of statistical humor designed to be an instructional aid.
This book is intended for introductory statistics courses for students in education and behavioral sciences.
* skewness and kurtosis measures;
* inferences about two dependent proportions and two independent means with unequal variances;
* homogeneity of variance tests;
* layout of the data in ANOVA models;
* the ANOVA linear model;
* a wide variety of multiple comparison procedures;
* significance tests in multiple linear regression; and
* extensive discussion of assumptions and how to deal with assumption violations.
Numerous tables and figures help illustrate concepts and present examples within the text. An extensive bibliography is included. A number of pedagogical devices are included to increase the reader's conceptual understanding of statistics: chapter outlines; list of key concepts for each chapter; chapter objectives; numerous realistic examples; summary tables of statistical assumptions; extensive references; and end of chapter conceptual and computational problems.
An instructor's manual is available containing answers to all of the problems, as well as a collection of statistical humor designed to be an instructional aid.
This book is intended for introductory statistics courses for students in education and behavioral sciences.
More details
Language
English
Place of publication
Mahwah
United States
Publishing group
Taylor & Francis Inc
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 254 mm
Width: 178 mm
ISBN-13
978-0-8058-2749-1 (9780805827491)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions

Debbie L. Hahs-Vaughn | Richard G. Lomax
An Introduction to Statistical Concepts
Book
04/2007
2nd Edition
Lawrence Erlbaum Associates Inc
€94.28
Article exhausted; check for reprint
Additional editions
Richard G. Lomax
Instructor's Guide for Introduction to Statistical Concepts for Education and the Behavioral Sciences
Book
07/2000
Lawrence Erlbaum Associates Inc
Unfortunately, price unknown
Article exhausted; check different version
Content
Contents: Preface. Introduction. Data Representation. Univariate Population Parameters and Sample Statistics. The Normal Distribution and Standard Scores. Introduction to Probability and Sample Statistics. Introduction to Hypothesis Testing: Inferences About a Single Mean. Inferences About the Difference Between Two Means. Inferences About Proportions. Inferences About Variances. Bivariate Measures of Association. Simple Linear Regression. Multiple Regression. One-Factor Analysis of Variance--Fixed-Effects Model. Multiple-Comparison Procedures. Factorial Analysis of Variance--Fixed-Effects Model. Introduction to Analysis of Covariance: The One-Factor Fixed-Effects Model With a Single Covariate. Random- and Mixed-Effects Analysis of Variance Models. Hierarchical and Randomized Block Analysis of Variance Models.