“Randomization-based approaches to probability and statistical inference” presented by Helen Burn (Mathematics)
Having a practical understanding of statistics is important for everyone given that we are awash in data. Inferential statistics is the art of using sample data to make inferences about a population or to determine whether differences between two groups are “statistically significant.” Yet educational research shows that traditional approaches to teaching statistical inference (t tests that rely on the Central Limit Theorem) are ineffective in helping people understand the core logic of inference. As a result, there is a growing movement towards using randomization-based approaches. This session will have two to three hands-on activities to demonstrate this approach and requires no formal understanding of statistics.
Location: Building 3, room 102
Students wishing to register for Science Seminar may take it for credit as Ge Sc 190/1 (items 6094 and 6096 respectively).
Science Seminar is a weekly set of presentations by Highline faculty about an area in their field of expertise. Designed to illustrate the cutting edge of science, technology and medicine for a general audience, the series is open to the public but also can be taken for college credit. In some cases faculty from outside the sciences illustrate how science and technology impact their field.