R Programming for Statistics and Data Science
R Programming for Data Science & Data Analysis. Applying R for Statistics and Data Visualization with GGplot2 in R
4.53 (5502 reviews)
30 800
students
6.5 hours
content
Aug 2023
last update
$84.99
regular price
What you will learn
Learn the fundamentals of programming in R
Work with R’s conditional statements, functions, and loops
Build your own functions in R
Get your data in and out of R
Learn the core tools for data science with R
Manipulate data with the Tidyverse ecosystem of packages
Systematically explore data in R
The grammar of graphics and the ggplot2 package
Visualise data: plot different types of data & draw insights
Transform data: best practices of when and how
Index, slice, and subset data
Learn the fundamentals of statistics and apply them in practice
Hypothesis testing in R
Understand and carry out regression analysis in R
Work with dummy variables
Learn to make decisions that are supported by the data!
Have fun by taking apart Star Wars and Pokemon data, as well some more serious data sets
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Our Verdict
The R Programming for Statistics and Data Science course stands out with its unique blend of programming fundamentals and statistical analysis, presented in a well-organized package by an experienced instructor. While some statistics concepts might be rushed or insufficiently explained, students have access to valuable hands-on exercises that facilitate learning. However, this course could benefit from enhanced documentation for code examples and better synchronization between exercise releases and course progression.
What We Liked
- Comprehensive coverage of R programming and statistical analysis
- Well-organized course material, clear instructions and concise explanations
- Hands-on exercises with practical examples and helpful tips
- Expert instructor with strong background in statistics
Potential Drawbacks
- Some statistics concepts could be explained more thoroughly
- Occasional discrepancies between exercise availability and course progression
- Lack of documentation for the course code examples
Related Topics
1562640
udemy ID
20/02/2018
course created date
27/07/2019
course indexed date
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