This course is intended for students in the
Biomedical Research Ph.D. program.
Students in this course will learn the basics of data exploration, presentation, and analysis suitable for biomedical researchers. We will focus on
interpretation of data, and on presenting results in a form suitable for publication in peer-reviewed manuscripts.

Class time:

Friday 10-10:50 am. Monday and Wednesday 10-10:50 am as needed.

Class meeting room:

Byrd Biotechnology and Science Center Room 336R

**Course director and instructor:**James Denvir, Ph.D.

Email:

Office:

BBSC 336R

Phone:

304-696-7327

**Course instructor:**Andrew Nato, Ph.D.

Email:

Office:

BBSC 336M

Phone:

304-696-3562

This course will use online materials; there is no text book. Class time will typically involve students sharing
material they about which they were confused or had questions, with discussion, and a preview by the instructor(s)
of the material to be covered before the next class.

Students will use the R statistical computing environment
for data analysis and visualization. For help with R and RStudio, use the
R Resources button on the navigation bar, in addition to material provided in class.

Assignment | Due Date | Model solution | R code |
---|---|---|---|

Creating an R Script | January 15^{th}, 2024 | ||

Computing measures of central tendency and spread | January 18^{th}, 2024 |
Solution | Solution |

Comparing data sets to the normal distribution | January 23^{rd}, 2024 |
Solution | Solution |

Exploring box plots with ggplot2 | January 25^{th}, 2024 |
Solution | Solution |

Bar graphs with error bars | February 15^{th}, 2024 |

Installing R and R studio:

These are some (of very many) free online
tutorials available which make good background reading:

- Tutorials from the University of Edinburgh coding club (start with the two introductory R tutorials)
- Quick-R tutorial
- Introductory R tutorial from Kelly Black at UGA
- Data Carpentry tutorials: for Genomics, or for ecology (the contents are pretty similar for both)