1. This lecture covers the Chi-squared, Student-t and F random variables. Since students in past semesters have had a hard time understanding this material I've extended what used to be a 15-minute segment of an in-class lecture into a 50 minute video. The content is the same: I simply go through it much slower and provide some simulation examples in R to cement the intuition.

    # vimeo.com/120308354 Uploaded 567 Plays 0 Comments
  2. This video covers material from Lecture 10 (Fall 2013) of Econ 103 at UPenn. It covers the law of iterated expectations example, as well as the covariance calculation example. The video ends with a proof that independence implies zero covariance. This proof is no longer in my lecture slides for Econ 103 so you're not responsible for it on exams, but you may find it interesting nonetheless.

    # vimeo.com/76565920 Uploaded 156 Plays 0 Comments
  3. This is a complete video recording of Lecture #2 of Econ 103 from the Spring Semester of 2015.

    # vimeo.com/117195343 Uploaded 753 Plays 0 Comments
  4. This is a video addendum to Lecture #8 from the Spring Semester of 2015. I ran out of time in class and didn't have time to cover the material on functions of random variables and calculating their expectation. This video covers the material I had to skip in class.

    # vimeo.com/119586397 Uploaded 298 Plays 1 Comment
  5. This is a complete video recording of Lecture #9 of Econ 103 in the Spring semester of 2015. The video also contains a digression in which I do some simulations for the Binomial random variable in R that is not covered when I give this lecture live in class.

    # vimeo.com/119881985 Uploaded 1,534 Plays 4 Comments

Econ 103 - Statistics for Economists

Francis DiTraglia

This is a collection of videos covering lecture material from Econ 103 (Statistics for Economists) at the University of Pennsylvania. The course website, including problem sets, R tutorials, slides, and past exams, is available at the following url:


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