Welcome!
Welcome to the SSS wiki! This site holds the lesson plans, projects, teaching guides, and content for the UC Berkeley course Sense and Sensibility and Science (SSS). Although this wiki is written to be used by instructors at UC Berkeley, it can easily be adapted for use at other universities. Variants of SSS have already been taught at Harvard and UC Irvine and will soon be taught at UChicago as well!
You will need an account to view or edit pages on this wiki. Please log in or request an account. Please direct any inquiries to Winston Yin and Gabriel Perko-Engel.
Course Content
The full version of this course is fourteen weeks long and covers topics from philosophy, psychology, data science, and the natural sciences. The topics in this course are as follows. You will need an account to see the topics and lesson plans in more depth.
- 1.1 Introduction and When Is Science Relevant
- Democracy vs. epistocracy
- Facts vs. values
- 1.2 Shared Reality and Modeling
- Shared reality
- Raft vs. pyramid
- Evaluation of models
- Science vs. decree
- Scientific realism vs. anti-realism
- Operationalism, conventionalism, and realism
- 2.1 Senses and Instrumentation
- Validation of instruments through interactive exploration, triangulation with other instruments, and comparison with direct senses
- 2.2 Systematic and Statistical Uncertainty
- Measurement proxies as sources of systematic and statistical uncertainty
- 3.1 Probabilistic Reasoning & 3.2 Calibration of Credence Levels
- The value of partial and probabilistic information
- Words of estimative probability (probably, likely, definitely, etc.)
- [math]\displaystyle{ p }[/math]-values and statistical significance
- Error bars and confidence intervals
- Strategies to improve calibration of credence levels (feedback, AOT, growth mindset, etc.)
- 4.1 Signal and Noise & 4.2 Finding Patterns in Random Noise
- Signal-to-noise ratio
- [math]\displaystyle{ p }[/math]-hacking
- Look elsewhere effect
- Gambler's fallacy
- Hot-hand fallacy
- File drawer effect
- HARKing (hypothesizing after results are known)
- Effect size (as distinct from statistical significance)
- 5.1 False Positives and Negatives
- Thresholds between positive and negative detections
- Trade offs between false positives and negatives
- 5.2 Scientific Optimism
- Iterative progress
- 6.1 Correlation and Causation
- Causation as correlation under intervention
- Randomized controlled trials
- Different directions of causation
- Spurious correlations
- 6.2 Hill's Criteria (Causation in the Messy Real World)
- Natural experiments
- Hill's criteria for causation
- Causal networks
- 7.1 Causation, Blame, and Policy
- Singular and general causation
- Acts of omission vs. commission (and the omission bias)
- Status quo bias
- 7.2 Emergent Phenomena
- Global effects that arise through the interaction of small pieces (rather than general causation)
- Explanation at different scales
- Scientific reductionism
- 8.1 Orders of Understanding
- Orders of magnitude
- Multiple causes of comparable importance
- Orders of importance of causes
- Refinement of models using higher order descriptions
- Scale of impact of policies
- 8.2 Fermi Problems
- Fermi problems
- 9.1 Heuristics
- Base rate neglect
- Representativeness heuristic and conjunction fallacy
- Availability heuristic
- Bounded rationality
- 9.2 Biases
- Fundamental attribution error
- Conformity
- Obedience
- Temporal discounting
- 10.1 Confirmation Bias
- Selective exposure
- Biased assimilation
- Strategies for reducing confirmation bias (AOT, etc.)
- 10.2 Blinding
- Techniques for blind analysis
- Preregistration
- Registered replication
- Adversarial collaboration
- Peer review
- 11.1 Pathological Science
- The spectrum of poor research
- Langmuir's pathological science indicators
- 11.2 When Is Science Suspect
- The validity and reliability of social science metrics
- External validity
- The difficulty of creating and applying social science metrics in cross-cultural contexts
- How researchers' biases and backgrounds shape their research agendas
- 12.1 Wisdom of Crowds and Herd Thinking
- The Wisdom of Crowds effect removing independent biases via error cancellation
- How humans can engage in herd thinking to cluster around biased answers to group questions
- 13.1 Denver Bullet Study
- The Denver Bullet Study process of integrating factual analysis from experts with value ratings from different stakeholders
- 13.2 Deliberative Polling
- The deliberative polling process of having the general public make decisions as though they were experts
- 14.1 Scenario Planning
- The Scenario Planning process of predicting and responding to possible futures
- What makes good drivers to use in Scenario Planning
Sense & Sensibility & Science
From Sense & Sensibility & Science