Complex data require complex statistical analyses. Data that are large, messy, multi-dimensional, and in unconventional formats often require advanced data science approaches for proper rigorous analysis. This workshop will expand on participants' prior knowledge of basic R programming and statistics to teach advanced analyses, including statistical modeling, empirical statistical analyses, and basic machine learning. In this interactive workshop, participants will first learn the theory underlying analyses, then watch demonstrations of running analyses in R, and finally practice running analyses themselves. Note that prior knowledge of basic R and statistics are required to be successful in this workshop, such as completion of the BIOF098 workshop or the STAT101 course.
Upon completing the workshop, attendees will have the confidence, knowledge, and resources to
- Understand and fit statistical models (ANOVA, regression)
- Perform model selection
- Run empirical statistical analyses (bootstrapping, simulations, imputation)
- Understand and fit basic machine learning models
Researchers with basic knowledge or R and statistics seeking to expand their skillsets and/or move toward data science-focused roles.
Attendees should have basic knowledge of R and statistics to successfully complete this advanced workshop. Prior completion of the BIOF098 workshop or the STAT101 course will provide adequate background.
BIOF 097 | Practical Scientific Statistics
BIOF 098 | Introduction to Statistical Analysis in R
Although no grades are given for courses, each participant will receive Continuing Education Units (CEUs) based on the number of contact hours. One CEU is equal to ten contact hours. Upon completion of the course each participant will receive a certificate, showing completion of the workshop and 2.8 CEUs.
This workshop applies toward the Bioinformatics Curiosity digital badge.
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.