Doing Statistical Analysis

Christer Thrane holds a PhD in Sociology and is Professor at Inland Norway University of Applied Science – Inland School of Business and Social Sciences. His research interests include quantitative modeling studies in leisure, sports, and tourism. He has 25 years of experience teaching quantitative research methods, and he has written several textbooks on this topic.

• Acknowledgments1. What is statistical analysis from a research perspective?1.1 A statistical association: Covid-19 spread and residential property prices 1.2 Why do statistical analysis in research? The book’s purpose and pedagogical approach 1.3 Three types of statistical research questions: Descriptive, associational, and inferential1.4 Some key concepts you really should understand 1.5 Chapter summary, key learning points, and the organization of the rest of the book2. Descriptive research questions 2.1 Introduction and chapter overview2.2 What is typical? Three measures of central tendency: Mean, median, and mode2.3 Variables’ measurement levels: Continuous or categorical variables2.4 Ordinal variables: A third and special-case measurement level2.5 Visual presentation of descriptive statistics: Graphs 2.6 The concept of variation: Statistical spread for continuous variables2.7 Foreshadowing associational research questions: Descriptive statistics for subgroups 2.8 Chapter summary, key learning points, and further reading2.9 Executing statistical commands: do-files in Stata and syntax-files in SPSS2.10 Chapter exercises with solutionsAppendix A: Christmas beer data Appendix B: Soccer data Appendix C: Student exercise data 3. Associational research questions I: Bivariate analysis3.1 Introduction: The association between two variables, x and y3.2 A categorical x and a categorical y: Cross-tabulation3.3 A categorical x and a continuous y: ANOVA3.4 A continuous x and a continuous y: Regression analysis 3.5 An ordinal y and bivariate analysis3.6 The limitations of bivariate analysis: The need for statistical control for a third variable3.7 Experimental control for a third (and fourth) variable3.8 Chapter summary, key learning points, and further reading3.9 Do-files in Stata and syntax-files in SPSS3.10 Chapter exercises with solutions4. Associational research questions II: Multiple regression4.1 Introduction and chapter overview4.2 Statistical control for observational data: Two examples4.3 The multiple regression model and R24.4 Non-linear effects4.5 Interaction effects (moderator effects)4.6 Regression on experimental data4.7 A dummy y4.8 Chapter summary, key learning points, and further reading4.9 Do-files in Stata and syntax-files in SPSS4.10 Chapter exercises with solutionsAppendix A: Student exercise motive dataAppendix B: Student tourism dataAppendix C: Red wine data 5. Inferential research questions5.1 Introduction and chapter overview5.2 Samples, populations, and random sampling5.3 Repeated sampling and the normal distribution5.4 The 95 percent CI for descriptive statistics: Means and proportions5.5 The 95 percent CI for variable associations5.6 Verifying that random sampling and the Central Limit Theorem work as promised5.7 Hypothesis testing and the assessment of statistical significance5.8 Critical aspects of significance testing5.9 Chapter summary, key learning points, and further reading5.10 Do-files in Stata and syntax-files in SPSS5.11 Chapter exercises with solutions6. Doing quantitative research: Some tricks of the trade 6.1 Introduction and chapter overview6.2 Creating, recoding, and labeling new variables 6.3 Creating a new variable by combining existing variables6.4 Missing data and what to do about them6.5 Outliers: When too much information causes trouble6.6 The assumptions of regression analysis6.7 Effect sizes6.8 How to present and communicate statistical-association results6.9 Chapter summary, key learning points, and further reading6.10 Statistical commands: Do-files in Stata and syntax-files in SPSS6.11 Chapter exercises with solutionsAppendix A: Female student weight dataReferencesIndex