This course on Statistics Tutorials Using Python aims to teach learners the fundamentals of statistics and how to apply them using Python. By the end of the course, students will be able to analyze data, understand different types of data, visualize data using Matplotlib, and work with distributions and probability functions. The course employs a tutorial-based approach, covering topics such as measures of spread, descriptive and inferential statistics, data visualization, and the central limit theorem. This course is suitable for beginners looking to enhance their statistical analysis skills using Python.
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
