Introduction to Statistics in Psychology

Description

Introduction to Statistics in Psychology, 6th edition is a comprehensive, modern student guide to understanding and using statistics in psychological research. This edition has been significantly revised to incorporate the essential SPSS steps required for carrying out statistical analysis. Abstract: Focusing on the needs and teaching methods for both students and lecturers, this represents a complete package for teaching statistics to psychology undergraduates.  Read more... Content: Cover Contents Guided tour Introduction Acknowledgements 1 Why statistics? Overview 1.1 Introduction 1.2 Research on learning statistics 1.3 What makes learning statistics difficult? 1.4 Positive about statistics 1.5 What statistics doesnâ#x80 #x99 t do 1.6 Easing the way 1.7 What do I need to know to be an effective user of statistics? 1.8 A few words about SPSS Key points PART 1 Descriptive statistics 2 Some basics: Variability and measurement Overview 2.1 Introduction 2.2 Variables and measurement 2.3 Major types of measurement Key points Computer analysis 3 Describing variables: Tables and diagramsOverview 3.1 Introduction 3.2 Choosing tables and diagrams 3.3 Errors to avoid Key points Computer analysis 4 Describing variables numerically: Averages, variation and spread Overview 4.1 Introduction 4.2 Typical scores: mean, median and mode 4.3 Comparison of mean, median and mode 4.4 The spread of scores: variability Key points Computer analysis 5 Shapes of distributions of scores Overview 5.1 Introduction 5.2 Histograms and frequency curves 5.3 The normal curve 5.4 Distorted curves 5.5 Other frequency curves Key points Computer analysis6 Standard deviation and z-scores: The standard unit of measurement in statistics Overview 6.1 Introduction 6.2 Theoretical background 6.3 Measuring the number of standard deviations â#x80 #x93 the z -score 6.4 A use of z -scores 6.5 The standard normal distribution 6.6 An important feature of z-scores Key points Computer analysis 7 Relationships between two or more variables: Diagrams and tables Overview 7.1 Introduction 7.2 The principles of diagrammatic and tabular presentation 7.3 Type A: both variables numerical scores 7.4 Type B: both variables nominal categories7.5 Type C: one variable nominal categories, the other numerical scores Key points Computer analysis 8 Correlation coefficients: Pearson correlation and Spearmanâ#x80 #x99 s rho Overview 8.1 Introduction 8.2 Principles of the correlation coefficient 8.3 Some rules to check out 8.4 Coefficient of determination 8.5 Significance testing 8.6 Spearmanâ#x80 #x99 s rho â#x80 #x93 another correlation coefficient 8.7 An example from the literature Key points Computer analysis 9 Regression: Prediction with precision Overview 9.1 Introduction 9.2 Theoretical background and regression equations9.3 Standard error: how accurate are the predicted score and the regression equations? Key points Computer analysis PART 2 Significance testing 10 Samples and populations: Generalising and inferring Overview 10.1 Introduction 10.2 Theoretical considerations 10.3 The characteristics of random samples 10.4 Confidence intervals Key points Computer analysis 11 Statistical significance for the correlation coefficient: A practical introduction to statistical inference Overview 11.1 Introduction 11.2 Theoretical considerations