Information science Empirical Analysis by R (2nd edition)

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Information Science
A thorough explanation of the "correct" use of regression analysis with R! The second edition is now available with updated notation of R code and strengthened as a programming manual! Amid the growing importance of data science, including machine learning and econometrics, this book focuses on "causal analysis" and is structured so that related content fits in this theme. It thoroughly explains the "correct" use of regression analysis in social science, centered on economics. By narrowing down the theme to causal analysis by regression analysis, the mathematics required to be understood even by high school mathematics is minimized. In addition to many analysis examples, many examples, answers, and explanations are included. In addition to many analysis examples, many intuitive and visual explanations by numerical simulations are included. The appendix at the end of the book also includes information on how to download the statistical processing language R, so it can be used as a programming manual. In the second edition, the notation of R code is updated the notation of R code and adding more practical exercises using real data.