This repository contains personal notes on Statistical Inference, compiled to serve as a reference for theoretical concepts and practical applications. The notes cover fundamental and advanced topics in statistical inference, including estimation, hypothesis testing, and regression analysis.
Additionally, R and Python scripts will be added over time to provide practical examples illustrating the concepts discussed in the notes.
statistical_theory/
Contains notes on the theoretical foundations of statistical inference, including probability theory, parameter estimation, hypothesis testing, and confidence intervals.
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statistics_R/
R scripts demonstrating practical applications of the statistical concepts. -
statistics_python/
Python scripts for practical examples and simulations.
Statistical-Inference/
├── statistical_theory/
├── statistics_R/
├── statistics_python/
├── README.md
└── LICENSE
The notes are based on standard statistical texts and literature. Specific references are listed in the corresponding notes.
Expand notes to include advanced topics such as Bayesian inference and multivariate analysis
Undergraduate and graduate students in statistics, data science, or related fields
Researchers seeking concise reference material on statistical inference
Self-learners interested in both theory and practical implementation
These notes reflect my personal understanding and interpretation of statistical inference concepts.
The repository is intended as a study and reference tool, not as a replacement for textbooks or peer-reviewed literature.
This repository is distributed under the GNU General Public License v3.0 (GPL-3.0).