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Overall Score : 94 / 100

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Course Description

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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Instructor Details

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Roger D. Peng is a Professor of statistics 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 statistics. 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.

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Reviews

4.7

422 total reviews

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By Itsido C A on 29-Dec-17

This is a very good course for introducing R programming!

By Prashanth K on 20-Aug-17

Awesome Course. Took some time but it has helped me tremendously!

By Hafiz F A on 7-Mar-17

Really well organized and compact. A nice introduction to working with R. A plus for showing were to look for further resources.

By Elias P on 15-Jul-17

Nice introduction to R. No errors/irritations in the exercises or tests. The setup is flawless.

By Zakaria H on 7-Dec-17

It was a nice programming course to start with although did not have prior skills in programming. I believe that I will use the knowledge to improve my programming skills and hopefully become a data scientist and an expert on R programming

By Bodica S on 5-Mar-18

very detailed and very practical

By Antony L on 28-Oct-17

The lectures give a good foundation while the programming assignments challenge your problem solving. It is necessary to do extra research to finish the programming assignments correctly but in the end the assignments are the most rewarding and best driver for learning.

By Sergei A on 22-Sep-17

Good intro to R. Challenging programming assignments in Week 2 and 4.

By Saif H on 7-Dec-16

Nice introductory course to programming in R

By Aswin G S on 29-Nov-16

awesome course for beginners

By shahin on 24-Dec-16

Excelent course ! It is very fun in my view

By satyam s on 22-Jan-17

The course provides a good explanation on important concepts of R and the assignments are designed well to hone the Programming Skills needed to tread Datascience.