|Understanding Statistics in Psychology with SPSS||
Understanding Statistics in Psychology with SPSS
|75.70||approx. 7-9 days|
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.
· 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 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
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/
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,
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
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.
Dennis Howitt and Duncan Cramer are based at Loughborough University.