There are 0 repository under p-values topic.
A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.
Scikit-Learn's linear regression extended with p-values.
This package provides functions to create descriptive statistics tables for continuous and categorical variables.
Case study from UDACITY Data Scientist Nanodegree
🚩 Conformal Anomaly Detection for 'PyOD' models.
A collection of Stata scripts and dialog boxes
Multiple-Linear-Regression-1. Consider only the below columns and prepare a prediction model for predicting Price of Toyota Corolla.
Empirical Bayes factors for objective statistical evidence
Predictive analysis, with feature engineering, and machine learning (ML) algorithms, such as linear regression, applied to predict the final sale price of homes in Ames, IA from 2006-2010.
Experiments with fastai
Statistical Multivariate Regression Analysis to determine the effects of mortality, economic and social factors on life expectancy.
Identifying and avoiding common misinterpretations in using statistics
This project attempted to analyze if race and age had any effects on the frequency of mental health issues in older adults.
Supervised-ML---Multiple-Linear-Regression---Cars-dataset. Model MPG of a car based on other variables. EDA, Correlation Analysis, Model Building, Model Testing, Model Validation Techniques, Collinearity Problem Check, Residual Analysis, Model Deletion Diagnostics (checking Outliers or Influencers) Two Techniques : 1. Cook's Distance & 2. Leverage value, Improving the Model, Model - Re-build, Re-check and Re-improve - 2, Model - Re-build, Re-check and Re-improve - 3, Final Model, Model Predictions.
p-value calculators written for STAT 200 at UIUC
Statistics and R
Executed Regression modelling, hypothesis testing and statistical analysis to predict factors affecting credit card balances in a firm. Tools & technologies: ANOVA, p-value, R square
**Intro to Statistics**: Discover the fascinating world of statistics with this engaging and accessible guide. Perfect for beginners, this book covers everything from p-values and t-tests to machine-learning models like random forests. Learn through practical examples and R code snippets, and unlock the power of statistical analysis.
Independent Project - Kaggle Dataset-- I worked on the European Soccer Dataset, using SQL (SQLite) to read in the data and then data wrangling before running statistical analysis and hypothesis testing on questions of who helps earn the most points for their team.
Use the isthissignif python package to test whether or not your OLS regression model is "statistically significant" based on different criteria.
Assignment-04-Simple-Linear-Regression-1 Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Model Predictions using simple linear regression.
Statistical data analysis of microarray data of Pyrococcus Furiosus exposed to gamma irradiation.
Used libraries and functions as follows:
Probability and Statistics for Machine Learning
FIB-PE 2021-22 Q1 Probability and Statistics subject final project
Conducted statistical analysis on MechaCar, a new prototype suffering from production troubles, data to provide insights that may help the manufacturing team.
In this project, the model is save and reused for prediction. Also, it is being containerize with docker to be ready for deployment.
Eindhoven University of Technology (TU/e) course "Improving your statistical inferences" by Daniel Lakens on Coursera (completed Dec 2022).
Analyzing MechaCar production data with R in order to troubleshoot issues that are blocking AutoRUs' manufacturing process.
🐟 Statistical analysis of fish dimensions and weights implemented into linear regression (Ordinary Least Squares) predictive model