Download Notes & Code from here - https://github.com/TheiScale/YouTube-Video-Notes/blob/main/Statistics%20Full%20course%20notes.pdf
Python for Data Science Part 1
https://www.youtube.com/watch?v=LgW6Vla0kXA
Python for Data Science part 2
https://www.youtube.com/watch?v=nBcMngKLixY&t=55072s
Welcome to the complete Statistics for Data Science Full Course! In this 3+ hour video, we’ll take you through all the essential statistical concepts you need to master for a successful career in Data Science.
Course Timestamp:
00:00 - 03:31 - Introduction
03:32 - 12:36 - Real life use cases of Statistics & Data Science
12:37 - 13:23 - Types of Statistics
13:25 - 22:21 - Descriptive Statitsics & Practical examples
22:22 - 32:54 - Inferential Statitics & its common techniques
32:55 - 34:35 - Practice Questions level 1
34:55 - 38:40 - Measure of Central Tendency
38:42 - 54:10 - Mean - by using library and code
54:11 - 1:08:37 - Median - by using library and use case of median
1:08:38 - 1:20:24 - Mode & Scipy Library
1:20:25 - 1:21:40 - Practice Question level 2
1:21:41 - 1:27:00 - Measure of Dispersion
1:27:01 - 1:27:30 - Techniques of measure of variability
1:27:31- 1:29:50 - Measure of variability - Range
1:29:51 - 1:44:30 - Variance - using library and code
1:44:31 - 1:57:27 - Standard Deviation - use cases
1:57:28 - 1:59:30 - Practice Question level 3
1:59:31 - 2:04:25 - Gaussian Distribution / Normal Distribution
2:04:26 - 2:08:20 - Skewed Distribution - positive & negative skewed
2:08:21 - 2:10:52 - Uniform Distribution
2:10:53 - 2:13:54 - Bimodal Distribution
2:13:55 - 2:15:18 - Multimodal Distribution
2:15:19 - 2:25:54 - Various Data Distribution through code
2:25:55 - 2:29:57 - Estimate & its types
2:29:58 - 2:32:50 - Confidence Interval
2:32:51- 2:38:00 - Hypothesis Testing & its Mechanism
2:38:06 - 2:51:13 - P value & T -test
2:51:15 - 3:08:21 - Z test, Ztablle , practical use case via code
3:08:22 - 3:12:45 - Practice Question level 4
Why this course?
Designed for beginners but goes deep into advanced topics.
Includes practical exercises to apply your knowledge.
Perfect for students, professionals, and data enthusiasts wanting to build a solid foundation in statistics.
By the end of this video, you’ll have a strong understanding of key statistical methods and how to apply them to solve real-world data science problems. Be sure to practice alongside the tutorial and explore the additional resources provided in the description!
Hit the like button, subscribe for more data science content, and let’s get started!
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