In this presentation, the audience was introduced to the very basic method in econometrics - Ordinary Least Squares, and its use in finding lines of best fit in linear regression. Afterwards, we tested predictions made with it and calculated the Root Mean Square Error.
As always, the resources are at the bottom of the page, enjoy!
The full derivation can be accessed from the Berkeley website using the QR above, or the link in resources.
Resources:
Wikipedia Contributors. "Ordinary Least Squares." Wikipedia. Last modified January 25, 2024. https://en.wikipedia.org/wiki/Ordinary_least_squares.
Aishwarya Valse. "Ordinary Least Square (OLS) Method for Linear Regression." Medium. Published July 4, 2020. https://medium.com/analytics-vidhya/ordinary-least-square-ols-method-for-linear-regression-ef8ca10aadfc.
Mauriz S. "Simple Linear Regression and OLS: Introduction to the Theory." Towards Data Science. Published May 25, 2020. https://towardsdatascience.com/simple-linear-regression-and-ols-introduction-to-the-theory-1b48f7c69867.
University of California, Berkeley. "Derivation of the Ordinary Least Squares Estimator." Berkeley. Accessed January 23, 2024. https://are.berkeley.edu/courses/EEP118/current/derive_ols.pdf.
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