R-squared measure for categorical data goodness-of-fit analysis using the surrogate R-squared

Applying binary logistic regression to predict loan approval outcomes using applicant information such as marital status, credit history, and property area. The analysis focuses on identifying the most important predictors of loan approval while evaluating model performance and assumptions.

Applying multinomial logistic regression to predict student academic program type using socioeconomic and academic performance variables.

Analysis code for Nature Climate Change paper: A global assessment of actors and their roles in climate change adaptation

A term project of the Biostatistics (2022) at NYCU-IST.

Havayolu yolcu memnuniyetini etkileyen faktörlerin SPSS ve R kullanılarak istatistiksel analizi ve lojistik regresyon ile modellenmesi.

📂 A collection of resources that may be helpful for analyzing your categorical data (including trait data).

This Categorical Encoder App is a Streamlit-based web application designed to help data analysts and machine learning practitioners efficiently encode categorical data into numerical representations.

I’ve created this repository with small Python scripts that I’ve used, and tested for spatial analysis. These scripts contains categorical statistics to statistical trends for each pixel. Feel free to download and use them on your local machine. I also have a MATLAB version for some of them.

Exploratory Data Analysis using Python, Basics of Python, Python Fundamentals

Supplementary material for the article "Substantive individual differences in social desirability: Stability, change, and associations with personality traits and job satisfaction in a large-scale longitudinal survey"