Introduction to Research Methods and Data Analysis in Psychology

Description

This third edition of Introduction to Research Methods and Data Analysis in Psychology provides you with a unique, balanced blend of quantitative and qualitative research methods. Highly practical in nature, the book guides you, step-by-step, through the research process and is underpinned by SPSS screenshots, diagrams and examples throughout. Cover Contents List of figures Guided tour Preface Acknowledgements Publisher’s acknowledgements Part 1 Introducing research methods 1 Starting out in research Introduction 1.1 Why research? 1.2 A very brief history of science 1.3 Quantitative versus qualitative? 1.4 A brief introduction to methods in the social sciences 1.5 Planning research Further reading 2 Variables: definitions and measurement Introduction 2.1 Operationalising variables 2.2 Independent and dependent variables 2.3 The problem of error and confounding variables 2.4 Levels of measurement 2.5 Categorical and continuous variables Further reading 3 Reliability, validity, sampling and groups Introduction 3.1 Reliability 3.2 Validity 3.3 The role of replication in the social sciences 3.4 Populations and samples 3.5 The problem of sampling bias 3.6 Methods of sampling 3.7 Sample sizes 3.8 Control and placebo groups Further reading 4 Collecting data 1: interviews and observation Introduction 4.1 Interviewing 4.2 Types, purposes and structures of interviews 4.3 Interview techniques 4.4 Group discussions 4.5 Repertory grid techniques 4.6 Observation 4.7 Structured and non-participant observation 4.8 Participant observation Further reading 5 Collecting data 2: questionnaires and psychometric tests Introduction 5.1 Questionnaires 5.2 The first rule of questionnaire design: don't reinvent the wheel 5.3 General principles, types and structure of questionnaires 5.4 Writing questions and measuring attitudes 5.5 Psychometrics 5.6 Reliability 5.7 Validity 5.8 Psychometric tests Further reading 6 Collecting data 3: experimental and quasi-experimental designs Introduction 6.1 The role of experiments in psychology 6.2 Types of experiment 6.3 Identifying four sources of error in experiments 6.4 Four ways to reduce error in experiments 6.5 Types of experimental design 6.6 Running an experiment 6.7 Describing an experiment: a note about causality 6.8 Returning to the basics of design Further reading 7 E-research Introduction 7.1 Types of e-research 7.2 A warning – what is the population? 7.3 E-research and online topics 7.4 E-research and offline topics 7.5 Ethical issues in e-research Further reading Part 2 Analysing quantitative data 8 Fundamentals of statistics Introduction 8.1 Descriptive and inferential statistics 8.2 Measures of central tendency and dispersion 8.3 Probability 8.4 Levels of significance 8.5 The normal distribution 8.6 Understanding z-scores 8.7 Standard error 8.8 Parametric versus non-parametric tests Further reading 9 Entering and manipulating data Introduction 9.1 First steps with SPSS 9.2 The Data Editor window 9.3 Defining variables 9.4 Entering data 9.5 Saving and opening data files 9.6 Sorting and splitting files 9.7 Selecting cases 9.8 Recoding variables 9.9 Computing new variables Further reading 10 Graphical representation and descriptive statistics Introduction 10.1 Descriptive statistics 10.2 Simple and complex bar charts 10.3 Histograms 10.4 Pie charts 10.5 Box plots 10.6 Scattergrams 10.7 Editing charts 11 Bivariate analysis 1: exploring differences between variables Introduction 11.1 Theoretical issues in inferential statistics 11.2 Introducing the t-test 11.3 Calculating an independent groups t-test 11.4 Calculating a related t-test 11.5 Introducing non-parametric tests of difference 11.6 Calculating a Mann–Whitney U-test 11.7 Calculating a Wilcoxon test 12 Bivariate analysis 2: exploring relationships between variables Introduction 12.1 Introducing chi-square 12.2 Calculating chi-square 12.3 Introducing correlation coefficients 12.4 Calculating correlation coefficients 13 Analysis of variance (ANOVA) Introduction 13.1 Terminology and techniques 13.2 Calculating a one-way ANOVA 13.3 Calculating a two-way ANOVA 13.4 Calculating a mixed design ANOVA 13.5 Non-parametric alternatives – Kruskal–Wallis and Friedman 14 Multivariate analysis of variance (MANOVA) Introduction 14.1 When would you use MANOVA? 14.2 Introduction to MANOVA 14.3 Calculating a MANOVA 14.4 Running a discriminant function analysis Further reading 15 Regression Introduction 15.1 Terminology and techniques 15.2 Calculating multiple regression using SPSS Further reading on statistics Statistical test flowchart 16 Exploratory factor analysis (EFA) Introduction 16.1 What is a latent variable? 16.2 Fundamentals of EFA 16.3 What is the difference between factor analysis and PCA? 16.4 Creating scale scores manually Further reading 17 Introducing R and R commander Introduction 17.1 What is R? 17.2 Installing new R libraries 17.3 The R commander 17.4 Importing data into R 17.5 Getting started with R code 17.6 Making comments 17.7 Basic R commands 17.8 Vectors 17.9 Large and small numbers 17.10 Save your code 17.11 Creating and saving a data frame 17.12 Graphs 17.13 Independent t-test 17.14 Related t-test 17.15 Mann–Whitney test 17.16 Wilcoxon test 17.17 Chi square 17.18 Correlation and linear regression 17.19 Multiple regression 17.20 One-way ANOVA 17.21 Two-way ANOVA 17.22 Repeated measures ANOVA 17.23 Reshaping wide format data into long format 17.24 Exploratory factor analysis Further R resources Further reading Part 3 Analysing qualitative data 18 Fundamentals of qualitative research Introduction 18.1 Philosophical underpinnings: the old paradigm 18.2 Philosophical underpinnings: the new paradigm 18.3 Revisiting the qualitative versus quantitative debate 18.4 Limitations of the new paradigm for the social sciences 18.5 Varieties of qualitative methods and analysis Further reading 19 Transcribing, coding and organising textual data Introduction 19.1 Purposes and principles of transcription 19.2 Systems of transcription 19.3 Transcription as analysis 19.4 Coding qualitative data 19.5 Thematic analysis 19.6 Organising and presenting the analysis of textual data Further reading 20 Phenomenological research methods Introduction 20.1 The fundamentals of phenomenology: philosophical issues 20.2 The fundamentals of phenomenology: methodological issues 20.3 Searching for meaning: phenomenological psychology and the Duquesne School 20.4 Searching for meaning: interpretative phenomenological analysis (IPA) 20.5 Strengths, limitations and debates Further reading 21 Grounded theory Introduction 21.1 Introducing grounded theory 21.2 Collecting data 21.3 The dynamic nature of meaning making 21.4 Coding 21.5 Memo-writing 21.6 Theory development 21.7 Strengths, limitations and debates Further reading 22 Discourse analysis Introduction 22.1 The turn to language 22.2 Approaches to the study of discourse 22.3 Discursive psychology 22.4 Foucauldian discourse analysis 22.5 Strengths, limitations and debates Further reading 23 Life story and narrative research Introduction 23.1 The turn to narrative 23.2 Selecting informants 23.3 Collecting data 23.4 Triangulation 23.5 Analysing life story data 23.6 Writing a life story 23.7 Narrative practice and form 23.8 Strengths, limitations and debates Further reading 24 The use of computers in qualitative research Introduction 24.1 Use of computers in qualitative research 24.2 Qualitative analysis software 24.3 Introducing qualitative analysis software 24.4 Fundamentals of using QDA software 24.5 Controversies and debates Further reading 25 Mixed methods Introduction 25.1 Similarities between methods 25.2 Four models of (sequenced) mixed methods 25.3 Four models of triangulated methods 25.4 Blended or 'hybrid' methods 25.5 Q method 25.6 Other hybrid methods 25.7 A final comment Further reading Resources: Q method Part 4 Ethics and reporting fi ndings 26 The ethics and politics of psychological research Introduction 26.1 Ethical fundamentals 26.2 BPS Code of Human Research Ethics principles 26.3 Respect for the autonomy and dignity of persons 26.4 Scientific value 26.5 Social responsibility 26.6 Maximising benefit and minimising harm 26.7 Other named issues in the Code of Human Research Ethics 26.8 Research with (non-human) animals 26.9 Equal opportunities 26.10 Politics and psychological research 26.11 Evaluation research 26.12 The need for balance Further reading 27 Reporting and presenting findings Introduction 27.1 The standard scientific report style 27.2 An example quantitative report (with commentary) 27.3 Writing up qualitative research 27.4 Writing skills 27.5 Presenting research – writing for publication Further reading Appendix: Tables of critical values for statistical tests References Index A B C D E F G H I J K L M N O P Q R S T U V W Y Z