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Correspondence Analysis with python
This code cover most basic way to estimate best fit parameters for a given dataset and model by chi-square minimisation. This analysis based on Hubble dataset with Flat LCDM model with two parameters.
The data relates to several user actions or interests recorded on two variants of landing pages for an online news portal. The objective is to analyse these interests by performing statistical analyses to determine if one variant is more effective based on chosen metrics (A/B testing).
Course by Jacob O. Wobbrock
Hypothesis-Testing-Chi2-Test-Athletes-and-Smokers. Assume Null Hypothesis as Ho: Independence of categorical variables (Athlete and Smoking not related). Thus Alternate Hypothesis as Ha: Dependence of categorical variables (Athlete and Smoking is somewhat/significantly related). As (p_value = 0.00038) < (α = 0.05); Reject Null Hypothesis i.e. Dependence among categorical variables Thus Athlete and Smoking is somewhat/significantly related.
Program to analyze transfer loss across domains using TF-IDF vectors with Chi squared into logistic regression model.