Category: R

R: Correlation and regression

PDF Copy of the Correlation and regression notes

We’ve been learning about different aspects of R – how to bring data in, how to clean the data, and how to graph the data.  Providing us with the basics of manipulating our data and visualizing it.  Remember though that R is a system that is used for statistical computation as well as graphics.  What makes is a robust system is that it includes a programming language, graphics, interfaces or connection opportunities with other languages, and debugging capabilities.  Although we can use R for many different purposes we can also use it for our statistical needs.

To start the statistical side of things, today we will see how we can use R to create correlations and regressions with our data.  We will use Fisher’s Iris dataset as the sample data to take us through correlations and regressions.

Download the R Script file used to work through this section of the R program.

Let’s work through the R script file in R Studio.  I will add tricks and tips that I’ve learned in the sample at a later date.  Please note that the R-script file contains comments throughout to guide you through it.

Enjoy!
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R: Data Wrangling

February 23, 2018 – session was taught by Andrew Frewin.  He took us through examples of different processes we may typically use to “wrangle” our research data.  Included in this post are two documents:

Please review the R Script file for comments on how each library and function was used in this session.

Next R-Users session will be on March 2.  We will be learning all about ggplot2

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R: RStudio and Importing Data

For this week’s R seminar, we will introduce the RStudio environment and discuss extending R with packages.  We will work through examples of how to import external data into R, with hands-on exercises.
The files we used in this session are linked below.  Please note that the R script file has comments within the File to help you run it and to explain what is happening at most steps.  For more detailed information on the packages and their functions, take advantage of the HELP and documentation that accompanies the packages.  Also note that due to the limitations of file types within this platform the R script file is saved as a PDF and not the original R script, note that the R script file is a text file.

 

Come and join us as we continue ‘R’ advertures!

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Andrew