Roll over image to zoom in Click on image to zoom

A PRactical Guide to Data Analysis

Name: A PRactical Guide to Data Analysis
Brand: SAGE PUBLICATIONS
SKU: 9781529792225
Price: 111.0 AUD
Availability: InStock

SAGE PUBLICATIONSISBN: 9781529792225

Using R and IBM SPSS Statistics

Price:

$111.00

Quantity:

By Paul Christiansen, Andrew Jones
Imprint: SAGE PUBLICATIONS
Release Date: March 13, 2026
Format: PAPERBACK
Dimensions: 246 x 174 mm
Weight:
Pages: 528

Share this product

Button Actions

Please copy the ISBN for submitting review copy form

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 all the statistics you need to know to pass your exam and do well at coursework

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

Helps to bridge the gap between using SPSS and R (or vice versa)

If you want to strengthen your grasp of statistics, overcome statistics anxiety or just pass your course - this is the guide for you.

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.

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

A PRactical Guide to Data Analysis

Request Academic Copy

Description

You may also like

Recently viewed