This repo is for a group project for the course MTH416A : Regression Analysis during the academic session 2021-2022 (even semester) at IIT Kanpur.

Ozone concentration and meteorology in the LA Basin, 1976 - A Regression Study [Report] [Presentation]

Prof. Sharmishtha Mitra, Department of Mathematics and Statistics, IIT Kanpur

• Arkajyoti Bhattacharjee
• Vishweshwar Tyagi
• Saurab Jain
• Apoorva Singh

• Among the parametric models, model A has the highest $R^2$ value as well as the lowest $RMSE$ value.
• All models - A, B and C are better than the baseline model Model 0. This validates our corrections for multicollinearity, heteroscedasticity and autocorrelation and variable selection.
• Simple non-parametric models are better if the problem of prediction is to be solved. But here, the ACE model transforms the data so that maximum $R^2$ can be achieved. And, as expected it has the highest $R^2$ value and the lowest $RMSE$ value amond all the models.
• So among the models considered here, ACE model is the best, both for the problem of prediction and for the purpose of explaining ozone concentration by the meteorological variables based on the ozone dataset.

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