Covers: application of Gauss-Markov Assumptions
Estimated time needed to finish: 8 minutes
Questions this item addresses:
  • What are some of the consequences of violation in GM assumptinos?
How to use this item?

A violation in GM assumptions can have business consequences because it will result in algorithmic bias. Imagine that in a hedge fund, as a data scientist, you are tasked with determining what dictates Airbnb overnight rental prices: Property type? The number of people it can accommodate? Distance of the property to city center? Cancellation policy? Having a wrong answer to that question may result in the fund purchasing properties that will not return maximum profit. To answer the question you can fit a Linear Regression model that predicts the prices and then perform a feature importance analysis. The result of the analysis may tell you that the most important features are, for example, the number of bathrooms and distance. The results of such analysis should be trusted only if the underlying assumptions are satisfied. For a more detailed discussion on this, refer to https://github.com/mtorabirad/PricePrediction/blob/master/project_predicting_AirBnB_prices.md

For more information on how these assumptions can be tested in Python, you can refer to. https://www.statsmodels.org/dev/examples/notebooks/generated/regression_diagnostics.html https://jeffmacaluso.github.io/post/LinearRegressionAssumptions/

URL: NA
Author(s) / creator(s) / reference(s)
Mahdi Torabi Rad
0 comment
Recipe
publicShare
Star(0)

Linear Regression

Contributors
Total time needed: ~37 minutes
Objectives
you learn the assumptions behind linear regression and, more importantly, what will occur if those assumptions are violated.
Potential Use Cases
refreshing knowledge on linear regression, preparing for job interview questions
Who is This For ?
BEGINNERpeople entering the field of data science and data scientists who think stat is their weak point
Click on each of the following annotated items to see details.
Resources4/4
WRITEUP 1. What is linear regression
  • What is linear regression?
10 minutes
WRITEUP 2. Ordinary Least Squares
  • What is Ordinary Least Squares?
10 minutes
WRITEUP 3. Homoscedasticity and error normality
  • Why do we need homoscedasticity and error normality assumptions?
9 minutes
ARTICLE 4. Potential business consequences of violation in GM assumptinos
  • What are some of the consequences of violation in GM assumptinos?
8 minutes

Concepts Covered

0 comment