Basic Statistics for Psychologists
Published on 8. June 2011
Book
Paperback/Softback
432 pages
978-0-230-27542-3 (ISBN)
Description
The emphasis upon methods of statistical research in psychology is often overlooked by beginning undergraduate students and subsequently, many find difficulty in approaching this unexpected yet so often integral topic of any given psychology degree. Subsequently this clearly written and comprehensive textbook offers itself as a guide to those students looking for a clear introduction on how to use statistics in psychological research. Crucially, students will be equipped with the key methods of statistical inference and learn how to interpret the results of various statistical tests. Expect to learn how to summarise data using the frequency distribution, measures of central tendency, variability as well how to employ the t-test and non-parametric tests for various types of groups and samples.
This core adoptable textbook covers all areas of undergraduate statistics, with good formulas and explanations for calculations and will aid students with the knowledge and tools necessary to developing their ability to conduct reliable and methodical research using statistics. This is an incredibly helpful and informative read for undergraduate students taking research methods and statistics courses in psychology.
Reviews / Votes
"A comprehensive core text that covers all areas of undergraduate statistics and is easy to read. The formulas and calculations are well-presented and explained with a clear overall approach and a logical order of topics. It is a useful resource for psychology students and a helpful introduction to statistics in general." - Toon Cillessen, Nijmegen, Netherlands "I very much liked the overall approach of the book. It is well structured and student friendly." - Judi Smith, School of Psychology, University of Liverpool "This book is extremely accessible and easy to read, using interesting examples throughout to demonstrate concepts and mathematical processes. What I particularly like is the balance between clear definitions, a friendly style and intuitive explanations." - Tamaryn Menneer, School of Psychology, University of SouthamptonMore details
Edition
1st ed. 2011
Language
English
Place of publication
London
United Kingdom
Publishing group
Bloomsbury Publishing PLC
Target group
Professional and scholarly
Illustrations
339
339 s/w Abbildungen
339 Illustrations, black and white; 432 p. 339 illus.
Dimensions
Height: 0 mm
Width: 0 mm
Weight
832 gr
ISBN-13
978-0-230-27542-3 (9780230275423)
DOI
10.1007/978-0-230-34592-8
Schweitzer Classification
Other editions
New editions
Marc Brysbaert
Basic Statistics for Psychologists
Book
10/2019
2nd Edition
Red Globe Press
€57.00
Article not available at the moment
Person
MARC BRYSBAERT is currently Research Professor of Psychology at Ghent University, Belgium. Previously he was Professor of Psychology at Royal Holloway, University of London, where he taught both statistics and research methods and developed this textbook.
Marc has extensive publishing experience and has written the market-leading book on 'Conceptual and Historical Issues in Psychology', published by Pearson, as well as a Dutch Handbook of Psychology, and more.
Marc has extensive publishing experience and has written the market-leading book on 'Conceptual and Historical Issues in Psychology', published by Pearson, as well as a Dutch Handbook of Psychology, and more.
Content
Preface.- Using statistics in psychology research.- Summarising data using the frequency distribution.- Summarising data using measures of central tendency.- Summarising data using measures of variability.- Standardised scores, normal distribution and probability.- Using the t-test to measure the difference between independent groups.- Interpreting the results of a statistical test.- Using non-parametric tests to measure the difference between independent groups.- Using the t-test to measure change in related samples.- Using non-parametric tests to measure change in related samples.- Improving predictions through the Pearson correlation coefficient.- Improving predictions through non-parametric tests: The Spearman rank correlation and the chi-square test for independence.- Using analysis of variance (ANOVA) to compare more than two conditions.- Post-hoc tests in ANOVA and multiple regression analysis.