Overview

Using statistics to analyse research data can be tricky when you are getting started. This book shows you how to effectively conduct statistical analysis in both R and SPSS without getting overwhelmed by complex theories and formulas. It is a practical manual that uses worked examples to help you get to grips with running statistical tests using commonly used software. Straightforward and clear, it assumes no prior knowledge and calmly takes you from reading the first page to completing your own analysis. It also: Covers a range of statistics taught at undergraduate level.  Presents varied, adaptable solutions to common problems. Embeds road-tested best practice into every stage of your analysis.  Provides you with programming skills that boost your employability. Gives any essential theory in a simple, easy to follow, manner. Supports understanding and communicating findings effectively. Helps to bridge the gap between using SPSS and R. If you want to strengthen your grasp of statistics, overcome statistics anxiety or just pass your course - this is the guide for you. 

Full Product Details

Author:   Christiansen ,  Andrew Jones
Publisher:   Sage Publications Ltd
Imprint:   Sage Publications Ltd
ISBN:  

9781529792232

ISBN 10:   1529792231
Pages:   512
Publication Date:   26 December 2025
Audience:   College/higher education ,  Undergraduate
Format:   Hardback
Publisher's Status:   Forthcoming
Availability:   Not yet available  
This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release.

Table of Contents

Chapter 1: The SPSS and R studio working environments Chapter 2: Central tendency and dispersion Chapter 3: General statistical tools (Distributions and Outliers) Chapter 4: Chi square (?2) Chapter 5: Correlating variables Chapter 6: Linear Regression part one Chapter 7: Linear Regression part two, hierarchical and assumption checking Chapter 8: Logistic regression Chapter 9. Comparing a sample distribution against a reference value (one-sample tests) Chapter 10. Comparing two dependent samples Chapter 11: Comparing two independent samples Chapter 12: Comparing three or more dependent samples Chapter 13: Comparing three or more independent samples Chapter 14: Complex ANOVAs Chapter 15: Analysis of Covariance (ANCOVA) Chapter 16: Multivariate Analysis of Variance (MANOVA) Chapter 17: Reliability analysis Chapter 18: Dimension reduction and Exploratory factor analysis

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Author Information

Dr Paul Christiansen is a Senior Lecturer in Statistics in the Department of Psychology at the University of Liverpool. He is interested in research integrity with a particular focus on accurate measurement (psychometrics). He works across a range of fields in Psychology as well as medical research. Dr Andrew Jones is a Senior Lecturer in the Department of Psychology at the University of Liverpool. He is a psychologist and statistics expert with 10+ years experience in substance use and obesity research.

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