This document provides additional resources for learning R and data cleaning. It includes links to online courses, tutorials, and documentation about learning the basics of R and data preprocessing. Cleaning data is noted to be an important but time-consuming part of the data science process that can account for up to 80% of the work. A variety of online resources are listed that provide information on cleaning data with R.

1. Quantitative
Methods
for
Lawyers
R Boot Camp - Bonus
Additional Resources
Data Cleaning
professor daniel martin katz computationallegalstudies.com @ computational

2. Often you will not
know in advance
how to solve your
problem

3. Great news is that
there is amount
+∞
online content
to help you

4. http://rseek.org/

5. When you do not know how to do
something try your query here
http://stackoverflow.com/

6. or iteratively query google until
you find some documentation

7. also feel free to poke around
on Bloggers

8. Some Additional
Resources to
Learn

9. https://www.datacamp.com/courses/introduction-to-r

10. http://www.ats.ucla.edu/stat/r/seminars/intro.htm

11. http://www3.nd.edu/~mclark19/learn/Introduction_to_R.pdf

12. Data Cleaning /
Preprocessing is typically a
very important thing that
thwarts many inquiries

13. http://www.nytimes.com/2014/08/18/technology/for-big-data-scientists-hurdle-to-insights-is-janitor-work.html

14. “Cleaning up data to
the point where you
can work with it is a
huge amount of
work.
If you’re trying to
reconcile a lot of
sources of data that
you don’t control
like in this flight
search example, it
can take 80% of
your time.”
http://jvns.ca/blog/2014/06/19/machine-learning-isnt-kaggle-competitions/

15. http://blog.revolutionanalytics.com/2014/08/data-cleaning-is-a-critical-part-of-the-data-science-process.html

16. http://101.datascience.community/2013/03/22/r-commands-for-cleaning-data/

17. https://www.coursera.org/course/getdata

18. http://cran.r-project.org/doc/contrib/de_Jonge+van_der_Loo-
Introduction_to_data_cleaning_with_R.pdf