The course "Computational and Graphical Models in Probability" equips learners with essential skills to analyze complex systems through simulation techniques and network analysis. By exploring advanced concepts such as Exponential Random Graph Models and Probabilistic Graphical Models, students will learn to model and interpret intricate social structures and dependencies … [Read more...] about Computational and Graphical Models in Probability
Probability and Statistics
Statistics and Data Analysis with Excel, Part 2
This course is meant to be a direct continuation of "Statistics and Data Analysis with Excel, Part 1." Therefore, it is not recommended to take Part 2 unless you've also taken Part 1. Building on the topics learned in Part 1 of the course (probability, probability mass and density functions, the normal and standard normal distributions), this course dives into a more applied … [Read more...] about Statistics and Data Analysis with Excel, Part 2
Statistics and Data Analysis with R
This course is the third course in a 3-part specialization entitled "Statistics and Applied Data Analysis." The course is meant for those familiar with statistics but unfamiliar with the programming language R. The purpose of this course is to teach learners how to use the popular open-source (and thus, free) integrated development environment RStudio to perform basic and … [Read more...] about Statistics and Data Analysis with R
How Science Turns Data Into Knowledge
How Science Turns Data Into Knowledge teaches you how to evaluate scientific claims critically, address experimental limitations, and recognize the roles of trust and responsibility within research. During the course, you’ll explore the nuances of significance testing, scientific research methods, and science communication, emphasizing the importance of carefully interpreting … [Read more...] about How Science Turns Data Into Knowledge
Bayesian Computational Statistics
A rigorous introduction to the theory of Bayesian Statistical Inference and Data Analysis, including prior and posterior distributions, Bayesian estimation and testing, Bayesian computation theories and methods, and implementation of Bayesian computation methods using popular statistical software. Required Textbook: Gelman, A., Carlin, J. B., Stern, H. S., Rubin, D. B. (2013) … [Read more...] about Bayesian Computational Statistics
