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    Roger D. Peng, PhD

    Professor of Statistics and Data Sciences

    • Johns Hopkins University
    • http://www.biostat.jhsph.edu/~rpeng/
    • rdpeng

    Bio

    Roger D. Peng is a Professor of Biostatistics at the Johns Hopkins Bloomberg School of Public Health and a Co-Editor of the 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.

    Courses - English

    A Crash Course in Data Science

    Advanced R Programming

    Building Data Visualization Tools

    Building R Packages

    Building a Data Science Team

    Data Science Capstone

    Data Science in Real Life

    Developing Data Products

    Executive Data Science Capstone

    Exploratory Data Analysis

    Getting and Cleaning Data

    Importing Data in the Tidyverse

    Introduction to the Tidyverse

    Managing Data Analysis

    Mastering Software Development in R Capstone

    Modeling Data in the Tidyverse

    Practical Machine Learning

    R Programming

    Regression Models

    Reproducible Research

    Statistical Inference

    The Data Scientist’s Toolbox

    The R Programming Environment

    The Unix Workbench

    Visualizing Data in the Tidyverse

    Wrangling Data in the Tidyverse

    Courses - Arabic

    R البرمجة باستخدام لغة

    الحصول على البيانات وتنظيفها

    تحليل البيانات الاستكشافية

    مجموعة أدوات عالم البيانات

    Courses - French

    Cours intensif sur la science des données

    Gestion de l’analyse des données

    Courses - German

    Datenanalyse verwalten

    Ein Crashkurs in Datenwissenschaft

    Courses - Spanish

    Gestión del análisis de datos

    Courses - Russian

    Управление анализом данных

    Courses - Korean

    데이터 과학자의 도구 상자

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