Reuben Thomas, PhD
As we attempt to make discoveries, we test new hypotheses using experimental data and hope that a skeptical and discerning person would start to believe the claims we make. Hypothesis testing, a branch of statistics, is a step we can rely on to bolster our claims. In this workshop, you will gain a fundamental understanding of common hypothesis-testing concepts and terms, such as null hypothesis, alternative hypothesis, type I error, type II error, p-value, and power.
Intermediate Level: This is an intermediate workshop in the Biostats series. Prior experience with statistics and experimental design is required. See introductory workshop:
View the upcoming workshops in the Gladstone Bioinformatics Program.
Note: This workshop will be held over 2 days, September 14–15, 2020. Attendance in the first session is mandatory in order to attend the second session.
The Gladstone Data Science Training Program was started in 2018 to provide trainees with learning opportunities and hands-on workshops to improve their skills in bioinformatics and computational analysis. This program offers a series of workshops throughout the year to enable trainees to gain new skills and get support with their questions and data.
Diversity, Equity, and Inclusion
At Gladstone, we are committed to providing events and professional development activities that resonate with our community’s diverse members. Our goal is to develop creative programming that encompasses a wide variety of ideas and perspectives to inspire, educate, and engage with everyone within our walls.
We want to effect positive change through our events and activities by providing a platform for discussions on important topics related to increasing diversity and inclusiveness in the sciences.