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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Data Types - R Objects and Attributes
Skills You'll Learn
Critical Thinking, Data Analysis, Computer Programming, Rstudio, General Statistics, Programming Principles, Debugging, Problem Solving, Data Structures, Computer Programming Tools, Statistical Programming, R Programming
Reviews
4.5 (22,308 ratings)
- 5 stars68.06%
- 4 stars22.14%
- 3 stars5.82%
- 2 stars2.08%
- 1 star1.89%
RR
Feb 20, 2017
I am pleasantly surprised with the quality of this course. For a beginner, the Swirl exercises are incredibly helpful and I was able to build confidence in working with R because of them. Thank you!
YZ
Jul 16, 2020
This is course is probably my favorite out of the Data Science: Foundations using R specialization. There was plenty of opportunity to practice and further develop by burgeoning R programming skill.
From the lesson
Week 1: Background, Getting Started, and Nuts & Bolts
Taught By
Roger D. Peng, PhD
Professor of Statistics and Data Sciences
Jeff Leek, PhD
Chief Data Officer, Vice President, and J Orin Edson Foundation Chair of Biostatistics in Public Health Sciences
Brian Caffo, PhD
Professor, Biostatistics