Bayesian Modeling

Petri Nokelainen (petri.nokelainen@tuni.fi)

Learning material

Lectures [PPT]

Bayesian modeling with B-Course [PDF]

Data files [Folder]

Bayesian modeling with [brms] (new)

Readings

Gill, J. (2002). Bayesian methods. A Social and Behavioral Sciences Approach. Boca Raton : Chapman & Hall/CRC.

Lindley, D.V. (1971). Making Decisions. London : Wiley.

Wasserman, L. (2004). All of Statistics. A Concise Course in Statistical Inference. New York : Springer.

Articles

Linearity vs. non-linearity
Example 1: Nokelainen, P., Silander, T., Ruohotie, P., & Tirri, H. (2007). Investigating the Number of Non-linear and Multi-modal Relationships between Observed Variables Measuring a Growth-oriented Atmosphere. Quality & Quantity, 41(6), 869-890. [PDF]

Bayes Factor
Example 2: Pylväs, L., & Nokelainen, P. (2021). Academics perceptions of intercultural competence and professional development after international mobility. International Journal of Intercultural Relations, 80, 336-348. [PDF]

Bayesian Classification Modeling
Example 3: Nokelainen, P., Tirri, K., & Merenti-Välimäki, H.-L. (2007). Investigating the Influence of Attribution Styles on the Development of Mathematical Talent. Gifted Child Quarterly, 51(1), 64-81. [PDF]

Bayesian Dependence Modeling
Example 4: Tirri, K., Nokelainen, P., & Mahkonen, M. (2009). How Morality and Religiosity Relate to Intelligence: A Case Study of Mathematically Gifted Adolescents. Journal of Empirical Theology, 22(1), 70-87. [PDF]

Bayesian Unsupervised Model-Based Visualization
Example 5: Nokelainen, P., & Ruohotie, P. (2009). Non-linear Modeling of Growth Prerequisites in a Finnish Polytechnic Institution of Higher Education. Journal of Workplace Learning, 21(1), 36-57. [PDF]

Assignment (choose one)

1. Write an 1500 - 2000 words essay that describes a pratical scenario of applying one or all of the Bayesian approaches, presented during these lectures, to your own research. Here are few starting points: Try to formulate at least one quantitative research question / problem that could be solved with both Bayesian and traditional frequentistic modeling. Describe how you would use Bayesian modeling to solve the problem: Write about the method (including at least description of real or fictive sample, data collection, statistical procedures and which one of the Bayesian modeling approaches you choose to use). Compare traditional frequentistic and Bayesian modeling approach considering solving the problem(s). Try to ponder pros and coins of both approaches. Memorize lectures and read articles, at least those provided in the course. Refer to them using APA -style references.

2. Complete "Bayesian modeling with B-Course" exercises 4, 6 and 7.

3. Complete "Exercise 1" in the brms material [Rmd] [HTML].