- Practicum: [Distributions in R.](https://raw.githubusercontent.com/mhtess/psych201s/master/practicums/distributions.Rmd)

- [Download JASP](https://jasp-stats.org/download/)
- Watch tutorial on [Bayesian Binomial Test](https://www.youtube.com/watch?v=rchMvOGOW1k) and apply it to [this data set](http://web.stanford.edu/class/psych201s/psych201s/data/)
- Lindley (1993). [The Analysis of Experimental Data: The Appreciation of Tea and Wine.](http://www2.isye.gatech.edu/~brani/isyebayes/bank/lindleybayeslady.pdf)

- Practicum: [Generative models and basic functional programming in WebPPL.](https://raw.githubusercontent.com/mhtess/psych201s/master/practicums/generative-models.Rmd)

- Finish [Distributions in R.](https://raw.githubusercontent.com/mhtess/psych201s/master/practicums/distributions.Rmd)
- Brewer, Brenden. (2015) [The Great Statistical Schism.](http://quillette.com/2015/11/13/the-great-statistical-schism/) [blogpost]

- Practicum: [Bayes' Rule.](https://raw.githubusercontent.com/mhtess/psych201s/master/practicums/bayes-rule.Rmd)
- Practicum: [Inferences with Binomials (Part 1)](https://raw.githubusercontent.com/mhtess/psych201s/master/practicums/ch3.Rmd)
- Associated text: [Chapter 3](http://ebooks.cambridge.org/pdf_viewer.jsf?cid=CBO9781139087759A022&ref=false&pubCode=CUP&urlPrefix=cambridge&productCode=cbo)

- [Chapter 1: Basics of Bayesian analysis](http://ebooks.cambridge.org/pdf_viewer.jsf?cid=CBO9781139087759A010&ref=false&pubCode=CUP&urlPrefix=cambridge&productCode=cbo): Read pages 3-6; 11-12 (incl., Boxes 1.1, 1.2); Think about exercises on pg 5
- [Chapter 2: Getting started](http://ebooks.cambridge.org/pdf_viewer.jsf?cid=CBO9781139087759A017&ref=false&pubCode=CUP&urlPrefix=cambridge&productCode=cbo) Read only: section 2.2.1 (Pages 17-19; including Box 2.1)

- Practicum: [Inferences with Binomials (Part 2)](https://raw.githubusercontent.com/mhtess/psych201s/master/practicums/ch3_part2.Rmd)
- Associated text: [Chapter 3](http://ebooks.cambridge.org/pdf_viewer.jsf?cid=CBO9781139087759A022&ref=false&pubCode=CUP&urlPrefix=cambridge&productCode=cbo)

- Wagenmakers, Morey, Lee (in press). [Bayesian benefits for the pragmatic researcher.](https://osf.io/3tdh9/) *Current directions in Psychological Science*
- Optional: Lee (2014). [The "new statistics" are built on fundamentally flawed foundations](https://webfiles.uci.edu/mdlee/Lee2014_NewStatistics.pdf)

- Practicum: [Inferences with Gaussians](https://raw.githubusercontent.com/mhtess/psych201s/master/practicums/ch4.Rmd)
- Associated text: [Chapter 4](http://ebooks.cambridge.org/pdf_viewer.jsf?cid=CBO9781139087759A029&ref=false&pubCode=CUP&urlPrefix=cambridge&productCode=cbo)

- Choose one:
- Morey, Hoekstra, Rouder, Lee, Wagenmakers (2015). [The fallacy of placing confidence in confidence intervals.](https://learnbayes.org/papers/confidenceIntervalsFallacy/fundamentalError_PBR.pdf) *Psychonomic Bulletin & Review*
- Hoekstra, Morey, Rouder, Wagenmakers (2014). [Robust misinterpretation of confidence intervals.](http://www.ejwagenmakers.com/inpress/HoekstraEtAlPBR.pdf) *Psychonomic Bulletin & Review* Optional readings:
- Miller and Ulrich (2015). [Interpreting confidence intervals: A comment on Hoekstra, Morey, Rouder, and Wagenmakers (2014)](http://link.springer.com/article/10.3758%2Fs13423-015-0859-7)
- Hoekstra, Morey, Rouder, Wagenmakers (2015). [Continued misinterpretation of confidence intervals: response to Miller and Ulrich.](http://orca.cf.ac.uk/84471/1/IOA-20152016-72.pdf)

- Practicum: [Regression](https://raw.githubusercontent.com/mhtess/psych201s/master/practicums/linear-regression.Rmd)
- Model: [Linear regression](https://raw.githubusercontent.com/mhtess/psych201s/master/practicums/webppl_models/linearRegression.wppl)
- Model: [Logistic regression](https://raw.githubusercontent.com/mhtess/psych201s/master/practicums/webppl_models/logisticRegression.wppl)
- Model: [Gibson & Wu (2013): Fixed effects](https://raw.githubusercontent.com/mhtess/psych201s/master/practicums/webppl_models/fixedEffects.wppl)
- Model: [Gibson & Wu (2013) Varying intercepts](https://raw.githubusercontent.com/mhtess/psych201s/master/practicums/webppl_models/varyingIntercepts.wppl)

- Sorensen, Hohenstein, Vasishth. (under review) [Bayesian linear mixed models using Stan: A tutorial for psychologists, linguists, and cognitive scientists.](http://www.stanford.edu/class/psych201s/psych201s/papers/SorensenEtAl.pdf)

- Practicum: [Mixture Models](https://raw.githubusercontent.com/mhtess/psych201s/master/practicums/ch6_part1.Rmd)
- Associated text: [Chapter 6: Latent Mixture Models (sections 6.1 - 6.4)](http://ebooks.cambridge.org/pdf_viewer.jsf?cid=CBO9781139087759A040&ref=false&pubCode=CUP&urlPrefix=cambridge&productCode=cbo)

- Practicum: [Mixture Models Pt. 2](https://raw.githubusercontent.com/mhtess/psych201s/master/practicums/ch6_part2.Rmd)
- Associated text: [Chapter 6: Latent Mixture Models (sections 6.5 - 6.7)](http://ebooks.cambridge.org/pdf_viewer.jsf?cid=CBO9781139087759A040&ref=false&pubCode=CUP&urlPrefix=cambridge&productCode=cbo)

- Practicum: [Ch. 7 exercises (Sections 7.1, 7.2, 7.3)](http://ebooks.cambridge.org/pdf_viewer.jsf?cid=CBO9781139087759A049&ref=false&pubCode=CUP&urlPrefix=cambridge&productCode=cbo)

Read:

- [Chapter 7: Bayesian model comparison](http://ebooks.cambridge.org/pdf_viewer.jsf?cid=CBO9781139087759A049&ref=false&pubCode=CUP&urlPrefix=cambridge&productCode=cbo)

- Practicum: [Selected exercises from Ch. 8 & 9](https://raw.githubusercontent.com/mhtess/psych201s/master/practicums/ch8_and_9.Rmd)
- Associated text: [Chapter 8: Comparing Gaussian means](http://ebooks.cambridge.org/pdf_viewer.jsf?cid=CBO9781139087759A057&ref=false&pubCode=CUP&urlPrefix=cambridge&productCode=cbo)
- Associated text: [Chapter 9: Comparing binomial probabilities](http://ebooks.cambridge.org/pdf_viewer.jsf?cid=CBO9781139087759A061&ref=false&pubCode=CUP&urlPrefix=cambridge&productCode=cbo)

- Dienes and Mclatchie (2016). [Four reasons to prefer Bayesian over orthodox statistical analyses](http://web.stanford.edu/class/psych201s/psych201s/papers/Dienes,%20Mclatchie_2016.pdf)
- Optional: Wetzels et al. (2011) [Statistical Evidence in Experimental Psychology](http://www.ejwagenmakers.com/2011/WetzelsEtAl2011_855.pdf). *Perspectives on Psychological Science*

- Etz (2016, blogpost). [Understanding Bayes: How to cheat to get the maximum Bayes factor for a given p-value](https://alexanderetz.com/2016/06/19/understanding-bayes-how-to-cheat-to-get-the-maximum-bayes-factor-for-a-given-p-value/)
- Wagenmakers et al. (2011) [Why Psychologists Must Change the Way They Analyze Their Data: The Case of Psi: Comment on Bem (2011)](http://web.stanford.edu/class/psych201s/psych201s/papers/Wagenmakers-etal-2011-bemComment.pdf)
- Bem, Utts, and Johnson (2011). [Must Psychologists Change the Way They Analyze Their Data?](http://web.stanford.edu/class/psych201s/psych201s/papers/Bem2011.pdf)
- Wagenmakers et al. (2011) [Yes, Psychologists Must Change the Way They Analyze Their Data: Clarifications for Bem, Utts, and Johnson (2011)](http://web.stanford.edu/class/psych201s/psych201s/papers/ClarificationsForBemUttsJohnson.pdf)
- [Chapter 13: Extrasensory Perception](http://ebooks.cambridge.org/pdf_viewer.jsf?cid=CBO9781139087759A079&ref=false&pubCode=CUP&urlPrefix=cambridge&productCode=cbo)

- Gigerenzer, G. and Marewski, J. N. (2015). [Surrogate Science: The Idol of a Universal Method for Scientific Inference](http://www.dcscience.net/Gigerenzer-Journal-of-Management-2015.pdf)

- Gershman, S. J. (2016) [On the blessing of abstraction.](http://gershmanlab.webfactional.com/pubs/abstraction.pdf)