In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.
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In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessar...
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Who is the instructor? Is Roger D. Peng, PhD a SCAM or a TRUSTED instructor?
Simply Statistics blog. He received his Ph.D. in Statistics from the University of California, Los Angeles and is a prominent researcher in the areas of air pollution and health risk assessment and statistical methods for environmental data. He is the recipient of the 2016 Mortimer Spiegelman Award from the American Public Health Association, which honors a statistician who has made outstanding contributions to health statistics. He created the course Statistical Programming at Johns Hopkins as a way to introduce students to the computational tools for data analysis. Dr. Peng is also a national leader in the area of methods and standards for reproducible research and is the Reproducible Research editor for the journal
Biostatistics. His research is highly interdisciplinary and his work has been published in major substantive and statistical journals, including the
Journal of the American Medical Association and the
Journal of the Royal Statistical Society. Dr. Peng is the author of more than a dozen software packages implementing statistical methods for environmental studies, methods for reproducible research, and data distribution tools. He has also given workshops, tutorials, and short courses in statistical computing and data analysis.