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Future Blog Post

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This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

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36-236: Probability and Statistical Inference II (Spring 2023)

Course, Statistics and Datascience Department, CMU, 2023

This is the second half of a two-semester, calculus-based course sequence that introduces theoretical aspects of probability and statistical inference to students. The course covers specific probability distributions and their inferential applications, starting with the normal distribution and continuing with the binomial and Poisson distributions, etc., and their use in point and interval estimation, hypothesis testing, and regression. Also covers topics related to multivariate distributions: marginal and conditional distributions, covariance, and conditional distribution moments.

36-225: Introduction to Probability Theory (Fall 2023)

Course, Statistics and Datascience Department, CMU, 2023

This is the first half of a year-long course which provides an introduction to probability and mathematical statistics for undergraduate students in the data sciences. Topics include elementary probability theory, conditional probability and independence, random variables, distribution functions, joint and conditional distributions, law of large numbers, and the central limit theorem.