Taking students on a journey of statistical discovery using R and R Studio, Andy Field's second edition of this popular text offers a friendly, engaging and practical resource with tools that allow students to practice and develop their skills and knowledge.
Taking students on a journey of statistical discovery using R and R Studio, Andy Field's second edition of this popular text offers a friendly, engaging and practical resource with tools that allow students to practice and develop their skills and knowledge.
Andy Field is a Reader in Psychology at The University of Sussex. He adores cats, listens to and plays loud music and enjoys teaching statistics. His ability to make statistics accessible and fun has been recognised with teaching awards from the University of Sussex (2001) and the British Psychological Society (2006).
Inhaltsangabe
Chapter 1: Why Is My Evil Lecturer Forcing Me to Learn Statistics? Chapter 2: The SPINE of statistics Chapter 3: The phoenix of statistics Chapter 4: ARGH! ARGH!Studio and Quarto Chapter 5: Describing and visualizing data Chapter 6: The beast of bias Chapter 7: Correlation Chapter 8: The linear model (regression) Chapter 9: Categorical predictors: Comparing two means Chapter 10: A tale of three Ms: Moderation, mediation, and missingness Chapter 11: GLM 1: Comparing several independent means Chapter 12: GLM 2: Comparing means adjusted for other predictors (analysis of covariance) Chapter 13: GLM 3: Factorial designs Chapter 14: GLM 4: Multilevel linear models Chapter 15: GLM 5: Repeated-measures designs Chapter 16: GLM 6: Mixed designs Chapter 17: Exploratory factor analysis Chapter 18: Categorical outcomes: chi-square and loglinear analysis Chapter 19: Categorical outcomes: logistic regression Chapter 20: Epilogue Appendix Glossary
Chapter 1: Why Is My Evil Lecturer Forcing Me to Learn Statistics? Chapter 2: The SPINE of statistics Chapter 3: The phoenix of statistics Chapter 4: ARGH! ARGH!Studio and Quarto Chapter 5: Describing and visualizing data Chapter 6: The beast of bias Chapter 7: Correlation Chapter 8: The linear model (regression) Chapter 9: Categorical predictors: Comparing two means Chapter 10: A tale of three Ms: Moderation, mediation, and missingness Chapter 11: GLM 1: Comparing several independent means Chapter 12: GLM 2: Comparing means adjusted for other predictors (analysis of covariance) Chapter 13: GLM 3: Factorial designs Chapter 14: GLM 4: Multilevel linear models Chapter 15: GLM 5: Repeated-measures designs Chapter 16: GLM 6: Mixed designs Chapter 17: Exploratory factor analysis Chapter 18: Categorical outcomes: chi-square and loglinear analysis Chapter 19: Categorical outcomes: logistic regression Chapter 20: Epilogue Appendix Glossary
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