Complete Statistics Course for Beginners | Data Science Tutorial | Sheryians AI School

Instructor in this video - Akarsh Vyas Complete Statistics for Data Science in One Video (5 Hours!) Master the most important statistics concepts required for Data Science, Machine Learning, and AI — all in one detailed, beginner-friendly crash course. In this video, we cover everything from descriptive statistics, probability, inferential statistics, to hypothesis testing, distributions, confidence intervals, correlation & regression, and more — explained with examples, visuals, and real-world data science context. GitHub link - https://github.com/AkarshVyas/youtube-Statistics Notes - https://drive.google.com/file/d/1MZoDojzmUtYz8GI9aeih-tCThCDKXwp0/view?usp=sharing ✅ Topics Covered: What is Statistics? Types of Data & Scales of Measurement Measures of Central Tendency (Mean, Median, Mode) Measures of Dispersion (Range, Variance, Standard Deviation, IQR) Probability & Conditional Probability Bayes' Theorem Probability Distributions (Normal, Binomial, Poisson) Hypothesis Testing (Z-test, T-test, Chi-square test, ANOVA) Confidence Intervals Correlation vs Causation p-value and Statistical Significance Statistical Thinking for Machine Learning ...and much more! Whether you're a Data Science student, ML enthusiast, or preparing for interviews, this video has everything you need to understand statistics deeply. No prior experience needed — ideal for absolute beginners! Don't forget to like, comment, and subscribe for more in-depth tutorials on Data Science and AI. 00:00 - 00:25 - Introduction 00:25 - 34:02 - Statistical Visualization 34:02 - 43:18 - Measure of Central Tendency 43:18 - 54:13 - Measure of Spread 54:13 - 01:01:29 - Outliers 01:01:29 - 01:06:59 - 5 number summary 01:06:59 - 01:14:15 - Outliers Code 01:14:15 - 01:26:00 - Variance and Standard Deviation 01:26:00 - 01:38:09 - Density Curve 01:38:09 - 01:54:44 - Z score 01:54:44 - 02:01:15 - Basic Probablity 02:01:15 - 02:09:59 - Probablity Events 02:09:59 - 02:20:55 - Addition Rule and Multiplication Rule 02:20:55 - 02:38:19 - Conditional Probablity 02:38:19 - 02:48:03 - Bayes Theorem 02:48:03 - 03:08:04 - Hypothesis testing Basics 03:08:04 - 03:31:35 - Z-test 03:31:35 - 03:40:53 - Z-Test Code Implementation 03:40:53 - 03:50:52 - T-Test 03:50:52 - 03:58:04 - T-Test Code Implementation 03:58:04 - 04:09:34 - Two Sample Test 04:09:34 - 04:14:57 - Two Sample Test Code 04:14:57 - 04:29:19 - Chi Square Test 04:29:19 - 04:38:07 - Chi Square Test Code 04:38:07 - 04:48:05 - Annova Test 04:48:05 - 04:55:42 - Covariance and Correlation 04:55:42 - 04:56:00 - Outro