Statistical analyses are regularly required for nearly every quantitative scientific study. Although simple data analysis tools are tenable for small-scale analyses, more rigorous software can enhance analysis replicability, improve data management, and facilitate more advanced analysis techniques in addition to scaling up to larger datasets. One such program, R is a free, open-source software that is standard for data analysis across numerous fields. This course will provide an introduction for using R to perform statistical analyses.
Upon completing the workshop, attendees will have the confidence, knowledge, and resources to
- Create R projects to organize data and code
- Write R scripts to perform full data analysis starting from raw data, including:
- Importing, editing, cleaning, and summarizing data in R
- Performing diagnostic tests, including making diagnostic plots
- Conducting statistical analyses
- Creating basic plots to demonstrate statistical findings
- Find and understand online resources to learn more about R functionalities
Researchers who understand statistical concepts and have perhaps conducted analyses using Excel, SPSS, or similar and/or have taken BIOF 097, but have little to no experience using R.
BIOF 097 | Practical Scientific Statistics
100% tuition refund for registrations cancelled 14 or more calendar days prior to the start of the workshop.
50% tuition refund for registrations cancelled between 4 to 13 calendar days prior to the start of the workshop.
No refund will be issued for registrations cancelled 3 calendar days or less prior to the start of the workshop.
All cancellations must be received in writing via email to Ms. Carline Coote at email@example.com.
Cancellations received after 4:00 pm (ET) on business days or received on non-business days are time marked for the following business day.
All refund payments will be processed by the start of the initial workshop.