May 2-4, 2018: Beginner’s statistics in R
Description
This course has two objectives. First, it will introduce the participants to the basics of statistical experimental design, data analysis, and statistical inference. It will cover topics such as optimal allocation of resources, confidence intervals, hypothesis testing, and linear regression. Second, it will introduce the practical steps of statistical analysis using the open-source environment R. In addition to discussing basic data management tasks in R, such as reading in data and performing basic analysis, it also contains introduction to reproducible research using R markdown. The course will contain both lectures and practical hands-on exercises.
Target audience
- Target audience are experimental scientists with no prior knowledge of statistics or R. The course will use two textbooks:
-
- Bremer & Doerge. ‘Using R at the Bench: Step-by-Step Data Analytics for Biologists’, Cold Spring Harbor LaboratoryPress, 2015
- Diez, Barr, & Cetinkaya-Rundel. ‘OpenIntro Statistics’, free online
Reference
‘Points of Significance’ in Nature Methods
Speakers
- Meena Choi, Laurent Gatto, Olga Vitek
Schedule
Wednesday, May 2, 2018
- 12:30 p.m. Registration
- 1:30 p.m. Lecture: Introduction to Statistics, Olga Vitek
- 3:00 p.m. Refreshments
- 3:30 p.m. Introduction to R and RStudio, Laurent Gatto
- 5:00 p.m. R markdown, Laurent Gatto
- 6:00 p.m. Dinner
Thursday, May 3, 2018
- 8:00 a.m. Q&A
- 9:00 a.m. Data exploration, Laurent Gatto
- 10:30 a.m. Refreshments
- 11:00 a.m. Data exploration 2 (dplyr), Laurent Gatto
- 12:30 p.m. Lunch
- 1:30 p.m. Lecture : Principal of experimental design and statistical inference, Olga Vitek
- 3:00 p.m. Refreshments
- 3:30 p.m. Data visualization, Laurent Gatto
- 5:00 p.m. Extra practice, Laurent Gatto
- 6:00 p.m. Adjourn
Friday, May 4, 2018
- 8:00 a.m. Q&A
- 9:00 a.m. Basic statistics – randomization, statistical summaries, confidence interval, Meena Choi
- 10:30 a.m. Refreshments
- 11:00 a.m. Lecture : sample size, linear regression, and categorical data, Olga Vitek
- 12:30 p.m. Lunch
- 1:30 p.m. Statistical hypothesis test, analysis of categorical data, Meena Choi
- 3:00 p.m. Refreshments
- 3:30 p.m. sample size calculation, linear model and correlation, Msnbase, Meena Choi/Laurent Gatto
- 5:00 p.m. Wrap-up