Statistics for Data Science Learning

Welcome to the Statistics for Data Science Learning repository! This repository is designed to help learners understand and apply key statistical concepts in the context of data science. The materials here cover a variety of topics, from basic statistics to intermediate-level techniques used in data analysis and machine learning.

Table of Contents

• Repository Overview
• Installation
• Usage
• File Structure
• Contributing
• License

Repository Overview

This repository contains Jupyter notebooks with explanations, examples, and exercises on various statistical topics. The focus is on providing hands-on experience with real-world datasets and problem-solving techniques that are essential for data scientists.

Topics Covered

1. Basic Statistics

   • Descriptive statistics (mean, median, mode, etc.)
   • Probability distributions
   • Sampling and hypothesis testing

2. Intermediate Statistics

   • Regression analysis (linear, logistic)
   • Analysis of variance (ANOVA)
   • Time series analysis

Installation

To get started, clone this repository to your local machine:

git clone https://github.com/SURESHBEEKHANI/Statistics-For-Data-Science-learining.git