This book presents a complete exploration of statistical data analysis in R for a wide variety of social science disciplines and quantitative methods courses.
This book presents a complete exploration of statistical data analysis in R for a wide variety of social science disciplines and quantitative methods courses.
G. David Garson teaches advanced research methodology in the School of Public and International Affairs, North Carolina State University, USA. Founder and longtime editor emeritus of the Social Science Computer Review , he is president of Statistical Associates Publishing, which provides free digital texts worldwide. His degrees are from Princeton University (BA, 1965) and Harvard University (PhD, 1969).
Inhaltsangabe
1. Using and Abusing Data Analytics in Social Science 2. Statistical Analytics with R, Part 1 3. Statistical Analytics with R, Part 2 4. Classification and Regression Trees in R 5. Random Forests 6. Modeling and Machine Learning 7. Neural Network Models and Deep Learning 8. Network Analysis 9. Text Analytics; Appendix 1. Introduction to R and R Studio Appendix 2. Data Used in this Book
1. Using and Abusing Data Analytics in Social Science 2. Statistical Analytics with R, Part 1 3. Statistical Analytics with R, Part 2 4. Classification and Regression Trees in R 5. Random Forests 6. Modeling and Machine Learning 7. Neural Network Models and Deep Learning 8. Network Analysis 9. Text Analytics; Appendix 1. Introduction to R and R Studio Appendix 2. Data Used in this Book
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