List of Units

Overview
This is essentially our "grand plan" in terms of material to cover. We should definitely clean this up somewhat. We are likely to have to cut out material to some degree. I am in favor of making a note of what we had to cut out, and whether it is worth adding to the wiki later anyways when we have time (e.g. as a resource to students, after we provide them with a link to it).

Units to Run

 * Frequentist Statistics (Paul)
 * basic intuition on manipulating random variables (union bound, Markov, moment bounds, Chernoff)
 * analysis tools for understanding why different distributions occur in nature
 * central limit theorem
 * good intuition from information theory (including probably basic metric entropy)
 * useful frequentist tools like cross-validation (ties in with value of empiricism)
 * maybe martingale stuff (just for fun)
 * Bayesian Statistics (Jacob)
 * intuitive explanation of Bayes' rule
 * intuition for conditioning and marginalization
 * Bayesian causality
 * gain comfort with Bayesian updating by working through some trickier models (mixture models etc.)
 * intuition that inference can in general be hard
 * Bayesian Modeling (Jacob)
 * survey of common distributions and why they occur
 * currently: normal, poisson, gamma, Dirichlet, student-t, Pareto (power law)
 * plus related things like Bernoulli, multinomial / categorical, Beta
 * maybe also multivariate student-t, inverse Wishart, log-normal, and discussion of conjugate prior
 * for fun, if time permits: Gaussian processes and Dirichlet processes
 * Cognitive Biases (??)
 * cognitive biases and how to deal with them
 * make sure to document what is science and what is our own experience (both are good but we should help our students update appropriately)
 * Effective Conversations (Yan, Jacob)
 * different types of conversations
 * how to get the most out of a conversation when the goal is information exchange
 * how to get the most out of the more typical case of social bonding
 * Mastering a Skill (Yan, Jacob, Adam)
 * good strategies for mastering something
 * this is a good place to highlight various rationality skills
 * Probability for Humans (Paul)
 * using probability to evaluate real-world evidence
 * Planning and acting (Anna, Paul)
 * consequentialism
 * resource / time allocation
 * goal factoring
 * value of information
 * thinking on the margin
 * good place to talk about virtue of (self-)honesty
 * Internal Behaviorism / Life-Hacking (Critch?)
 * The Art of Estimation (Yan)
 * give people good heuristics for evaluating incoming information
 * this could potentially be part of the "Probability for Humans" unit

Guest Talks / Enrichment Lectures

 * Choosing Good Problems (Charles)
 * Building a Startup (Albert)
 * Problem-Solving in Linguistics (Adam)
 * Cognitive Science (Tom)
 * Bayesian Inference (Jacob?)

Other Topics Listed in Documents
These are things that it's unclear we should make units around, or that might be redundant. Feel free to remove things from this list as you see fit (meaning either turn them into a unit or just scrap them from the program, my MLE for each is on the latter).
 * Using Words / Being Specific? -- this could potentially get absorbed into an existing unit
 * Case Studies in Doing Things Excellently
 * Belief vs. Anticipation / Empiricism

List of Information We Want to Cover
NOTE: If something already naturally falls into a unit, I've put it in brackets. If I think it is better absorbed organically throughout camp than covered explicitly, I've marked it SDT [Show Don't Tell]. I also feel like things are probably missing from this list, so feel free to add to it.

Likely what this list is actually most useful for is so that we don't forget to include specific things that we think are important.
 * effective altruism / choosing a career
 * asking for what you want / what rules are
 * How to X for several X [Mastering a Skill / Guest Talks]
 * Self-improvement [Mastering a Skill]
 * Social dynamics, manuevering, social skills [Effective Conversations]
 * Virtues of empiricism / curiosity [SDT]
 * Agreement and learning from others [Effective Conversations]
 * Bayes to aggregate real info [goes with Probability for Humans, but I also think we should do a lab on this and potentially also have contests throughout the week]
 * Thinking like a mathematician / engineer / computer scientist / phycisist

Miscellaneous
This is where I put stuff that was in the google docs that I wasn't sure what to do with.

Agreement

Information theory

Decision theory