https://github.com/tlatkowski/tf-feature-selection

Implementation of various feature selection methods using TensorFlow library.

f-statistics f-test feature-extraction feature-importance feature-selection fisher mrmr pearson-correlation tensorflow tensorflow-experiments tensorflow-library ttest

Last synced: 25 Jun 2025

https://github.com/moindalvs/simple_linear_regression_1

Predicting Delivery Time Using Sorting Time

aic bic data-transformation f-statistics likelihood log-transformation matplotlib numpy ols-regression ordinary-least-squares pandas-dataframe pandas-library prediction predictive-modeling residuals rmse-score simple-linear-regression sklearn sklearn-library

Last synced: 17 Apr 2026

https://github.com/moindalvs/hypothesis_test_4

TeleCall uses 4 centers around the globe to process customer order forms. They audit a certain % of the customer order forms. Any error in order form renders it defective and has to be reworked before processing. The manager wants to check whether the defective % varies by centre. Please analyze the data at 5% significance level and help the manager draw appropriate inferences

anova-test f-statistics hypothesis-testing

Last synced: 18 Apr 2026

https://github.com/aditiisaxena/reservoir-water-level-analysis

Econometrics project that aims to analyze the relationship between Reservoir Water Level and various Power Inequalities in different states of India.

anova-analysis chow-test data-transformation dataset econometrics f-statistics maximum-likelihood-estimation monte-carlo-simulation r-language regression-models statistical-analysis t-test

Last synced: 04 Apr 2025

https://github.com/quickheaven/python-statsmodels-research

coefficients data-science f-statistics jupyter-notebook python r-square-values statistics statsmodels

Last synced: 14 Apr 2026

https://github.com/saboye/predicting-sales-performance

project to predict smartphone sales based on the marketing budget spent on advertising using three platforms involves collecting data on marketing spending and smartphone sales, and using statistical and machine learning techniques to build a model that can predict future smartphone sales based on changes in marketing budget.

f-statistics linear-regression p-values python r-square r-squared

Last synced: 01 May 2026