Learn essential statistical concepts and techniques using Python in this comprehensive tutorial series. Explore topics such as measures of spread, descriptive and inferential statistics, data types, data visualization with Matplotlib and Seaborn, probability distributions, central limit theorem, probability mass functions, and confidence intervals. Gain practical skills in data analysis and visualization through hands-on examples and applications in data science.
Overview
Syllabus
Statistics Using Python Tutorial Part 1 | Statistics with Python Tutorial | Data Science Tutorial #1.
Statistics Using Python Tutorial Part 2 | What is Measure of Spread | Data Science Tutorial #2.
Statistics Using Python Tutorial Part 3|Descriptive, Inferential Statistics|Data Science Tutorial #3.
Statistics Using Python Tutorial Part 4 | Types of Data in Statistics | Data Science Tutorial #4.
Statistics Using Python Part 5 | Data Visualization Using Matplotlib | Data Science Tutorial #5.
Statistics Using Python Tutorial Part 6 | Seaborn Python Tutorial | Data Science Tutorial #6.
Statistics Using Python Tutorial Part 7 | Types of Distribution | Data Science Tutorial #7.
Statistics Using Python Tutorial Part 8 | Central Limit Theorem | Data Science Tutorial #8.
Statistics Using Python Tutorial Part 9 | Probability Mass Function | Data Science Tutorial #9.
Statistics Using Python Tutorial Part 10 | Confidence Interval Statistics - Examples | Data Science.
Taught by
Acadgild
