YoVDO

What Beer and Running Taught Me About the Scientific Process - Christie Aschwanden at SFI

Offered By: Santa Fe Institute via YouTube

Tags

Statistics & Probability Courses P-values Courses

Course Description

Overview

Explore the intersection of science, sports, and journalism in this 47-minute talk by Christie Aschwanden at the Santa Fe Institute. Delve into the scientific method through the lens of beer's effects on running performance, as Aschwanden shares insights from her bestselling book "GOOD TO GO." Gain a deeper understanding of statistics, scientific methodology, and reproducibility challenges in research. Learn why approaching science with healthy skepticism is crucial for journalists. Examine the importance of study design, participant expectations, and the pitfalls of p-values in scientific research. Discover how science is an iterative, self-correcting process and why embracing uncertainty is essential. Reflect on the cultural aspects of science and the role of journalists in communicating scientific findings to the public.

Syllabus

Intro
Garfield Grumble
Beer
Beer Run
The Trial
Run to Exhaustion
How hard is it
How long
Hypothesis
Results
Study design really matters
Participants expectations are important
Being primed to believe
Pvalues and statistics
The problem with pvalues
American Statistical Association statement
P hacking interactive
Pvalues
Science is an iterative process
Science isnt broken
Science is selfcorrecting
Cultural aspects of science
How should we talk about science
Open to new change
Uncertainty
Science is always wrong
Thank you
The magic metric
People want an answer
Whos job is it
Talk to journalists
Being respectful


Taught by

Santa Fe Institute

Tags

Related Courses

Understanding Clinical Research: Behind the Statistics
University of Cape Town via Coursera
Improving your statistical inferences
Eindhoven University of Technology via Coursera
Understanding Data
Marginal Revolution University
Data Science: Inference and Modeling
Harvard University via edX
Simple Regression Analysis in Public Health
Johns Hopkins University via Coursera