Workshops generally run from 9:00am - 5:00pm.
Simultaneous access to two screens is highly recommended for best learning experience. Examples include one computer with two screens, two computers, one laptop and one tablet, etc.
As big data becomes the norm and experiments continue to increase in scale, proper understanding and use of statistics is becoming increasingly important for scientists in every field. While experimental researchers are expert in concepts related to their respective fields and receive extensive scientific education, statistical training is relatively lacking. As a result, experimental researchers may feel overwhelmed or uncertain about how to correctly use statistics to quantify their experimental results and how to properly interpret the results of those statistical tests. Unfortunately, this knowledge gap can result in both reduced understanding of reported results in scientific publications as well as superficial or potentially inaccurate reported statistics. This course serves as a practical, hands-on workshop to close the knowledge gap and help experimental researchers learn how to choose a statistical test for their data, how to perform those tests, and how to interpret the results. The workshop starts by establishing a solid foundation in basic statistical theory before advancing to practical applications of statistical tests on real data.
Upon completing the workshop, attendees will have the confidence, knowledge, and resources to:
- Understand basic theory underlying many popular statistical tests
- Determine the appropriate statistical test to use given a dataset and a research question
- Perform basic statistical tests
- Interpret and understand output from statistical tests
Experimental researchers with limited formal statistics instruction.
Attendees should have access to and basic knowledge of Excel. Analyses will also be demonstrated in SPSS and R, but no formal programming skills are required.
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 this course each participant will receive a certificate, showing completion of the workshop and 2.1 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 firstname.lastname@example.org.
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.