Understanding Statistics in Psychology with SPSS

Series
Pearson
Author
Dennis Howitt / Duncan Cramer  
Publisher
Pearson
Cover
Softcover
Edition
8
Language
English
Total pages
752
Pub.-date
March 2020
ISBN13
9781292282305
ISBN
1292282304
Related Titles


Product detail

Product Price CHF Available  
9781292282305
Understanding Statistics in Psychology with SPSS
75.70 approx. 7-9 days

Free evaluation copy for lecturers


Description

A clear and comprehensive introduction to Statistics with step by step guidance on using SPSS to carry out statistical analysis. Understanding Statistics in Psychology with SPSS 8th edition is geared towards helping students to properly understand statistical techniques so gaining the confidence to apply them with the help of SPSS.

Features

·    Comprehensive and practical coverage of statistics with step by step guidance of how to use SPSS to use SPSS to analyse data

·    Suitable for use with all versions of SPSS

·    Examples from a wide range of real psychological studies illustrate how statistical techniques are used in practice

·    Includes clear and detailed guidance on choosing tests, interpreting findings and reporting and writing up research

·    Student focused pedagogical approach including

o   Key concept boxes detailing important terms

o   Focus on sections exploring complex topics in greater depth

o   Explaining statistics sections clarify important statistical concepts.

New to this Edition

·    New chapter on Data Mining and Big Data

·    Updated SPSS screenshots throughout the book

·    Updated examples from a wide range of real psychological studies to illustrate how statistical techniques are used in practice

Table of Contents

Chapter 1    Why statistics?

 

Part 1  Descriptive statistics    

Chapter 2    Some basics: Variability and measurement   

Chapter 3    Describing variables: Tables and diagrams   

Chapter 4    Describing variables numerically: Averages, variation and spread   

Chapter 5    Shapes of distributions of scores   

Chapter 6    Standard deviation and z-scores: Standard unit of measurement in statistics

Chapter 7    Relationships between two or more variables: Diagrams and tables

Chapter 8    Correlation coefficients: Pearson’s correlation and Spearman’s rho

Chapter 9    Regression: Prediction with precision  

 

Part 2  Significance testing    

Chapter 10 Samples from populations

Chapter 11 Statistical significance for the correlation coefficient: A practical introduction to statistical inference  

Chapter 12 Standard error: Standard deviation of the means of samples  

Chapter 13 Related t-test: Comparing two samples of related/correlated/paired scores  

Chapter 14 Unrelated t-test: Comparing two samples of unrelated/uncorrelated/
  independent scores  

Chapter 15 What you need to write about your statistical analysis

Chapter 16 Confidence intervals

Chapter 17 Effect size in statistical analysis: Do my findings matter?

Chapter 18 Chi-square: Differences between samples of frequency data     

Chapter 19 Probability

Chapter 20 One-tailed versus two-tailed significance testing   

Chapter 21 Ranking tests: Nonparametric statistics

 

Part 3  Introduction to analysis of variance

Chapter 22 Variance ratio test: F-ratio to compare two variances  

Chapter 23 Analysis of variance (ANOVA): One-way unrelated or uncorrelated ANOVA   

Chapter 24 ANOVA for correlated scores or repeated measures   

Chapter 25 Two-way or factorial ANOVA for unrelated/uncorrelated scores:
  Two studies for the price of one?   

Chapter 26 Multiple comparisons with in ANOVA: A priori and post hoc tests   

Chapter 27 Mixed-design ANOVA: Related and unrelated variables together  

Chapter 28 Analysis of covariance (ANCOVA): Controlling for additional variables

Chapter 29 Multivariate analysis of variance (MANOVA)

Chapter 30 Discriminant (function) analysis – especially in MANOVA  

Chapter 31 Statistics and analysis of experiments

 

Part 4  More advanced correlational statistics  

Chapter 32 Partial correlation: Spurious correlation, third or confounding variables,
  suppressor variables   

Chapter 33 Factor analysis: Simplifying complex data  

Chapter 34 Multiple regression and multiple correlation   

Chapter 35 Path analysis

 

 

Part 5  Assorted advanced techniques

Chapter 36 Meta-analysis: Combining and exploring statistical findings
  from previous research

Chapter 37 Reliability in scales and measurement: Consistency and agreement

Chapter 38 Influence of moderator variables on relationships between two variables  

Chapter 39 Statistical power analysis: Getting the sample size right  

 

Part 6  Advanced qualitative or nominal techniques  

Chapter 40 Log-linear methods: Analysis of complex contingency tables 

Chapter 41 Multinomial logistic regression: Distinguishing between several
  different categories or groups  

Chapter 42 Binomial logistic regression

Chapter 43   Data mining and big data  

Back Cover

Learn to apply statistical concepts using SPSS with confidence

 

Understanding Statistics in Psychology with SPSS, 8th Edition, by Howitt and Cramer offers students a trusted, straightforward, and engaging way of learning to do statistical analyses confidently using SPSS. Comprehensive and practical, the text is organised into short accessible chapters, making it the ideal text for undergraduate psychology students needing to get to grips with statistics in class or independently.

 

Clear diagrams and full-colour screenshots from SPSS make the text suitable for beginners, while the broad coverage of topics ensures that students can continue to use it as they progress to more advanced techniques. This book combines coverage of statistics with full guidance on how to use SPSS to analyse data and is suitable for use with all versions of SPSS. Examples from a wide range of real psychological studies illustrate how statistical techniques are used in practice and the book includes clear and detailed guidance on choosing tests, interpreting findings and reporting and writing up research.

 

New to this edition:

●   New chapter on Data Mining and Big Data

●   Updated SPSS screenshots throughout the book

●   New and updated coverage of how to learn statistics

 

 

Dennis Howitt and Duncan Cramer are with Loughborough University.

 

Pearson, the world’s learning company.

Author

Dennis Howitt and Duncan Cramer are based at Loughborough University.