Here, you'll find tutorials and guides to help you learn about data analysis. Be sure to check your class materials (on Blackboard) and this info before asking our Data Lab experts for help.
R (programming Language) REFERENCES
Kelly Black R Tutorial
This is our recommended tutorial for clear instructions, in-depth explanations, and plenty of examples and code to follow. The sections on 'Input' and 'Basic Operations' are good starting points.
UCLA R Webpage
This is recommended by Dr. Becerril and provides many good learning modules. Under FAQs. you can find wide range of solutions including how to use some mildly complex procedures.
Quick-R by Data Camp
A beginner's guide to R basics with sample code and screen shots. Be sure to use the (not user-friendly) menu on the left for more detailed instructions - like 'Importing Data,' for example.
A collection of resources. The Venables book, An Introduction to R, is a nice text if you prefer longer explanations organized by chapters. The Maindonald text is also good, with more screenshots and visuals.
Machine Learning REFERENCES
UC Irvine Machine Learning Repository
The UCI Machine Learning Repository is a collection of databases, domain theories, and data generators that are used by the machine learning community for the empirical analysis of machine learning algorithms.