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Study mode:
on
1
Introduction
2
biomass distribution
3
all kinds of evidence
4
dependent on software
5
Continuous integration
6
Examples
7
Science vs Programming
8
A Serious Issue
9
P Hacking
10
Clinical Trials
11
Issues with Scientific Conduct
12
Fraud and Treason
13
Numerical Error
14
Excel
15
Cancer
16
Science is a Mess
17
The Basic Problem
18
The Things Not Taught
19
Example
20
Software Engineering
21
Software Carpentry
22
Data Integration
23
Unit Testing
24
Translation
25
Conclusion
Description:
Explore a thought-provoking lecture examining the parallels between scientific research and amateur software development. Delve into the contrast between science's remarkable success and academia's often chaotic practices. Discover how the professionalism of software engineering, particularly in open-source development, can enhance scientific work. Learn about the challenges faced in scientific conduct, including P-hacking, clinical trial issues, and numerical errors. Examine the importance of proper training for scientists in responsible work practices. Investigate how software engineering principles like continuous integration, unit testing, and data integration can be applied to improve scientific research. Gain insights into the potential for creating more robust, transparent, and reproducible scientific processes by adopting best practices from the software development world.

Science as Amateur Software Development

Richard McElreath
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