Take a deep dive into the fascinating world of statistics using Python with this well-curated course. It focuses on the calculation and practical application of descriptive and inferential statistics using Python's pandas, numpy, and scipy libraries.
Overview
Syllabus
- Lesson 1: Unveiling Measures of Centrality: A Descriptive Statistics Journey with Python
- Analyzing Age Group Dataset with Measures of Centrality
- Altering Dataset for Changing Measures of Centrality
- Calculating Mean and Median for a New Age Group
- Space Camp Age Analysis
- Lesson 2: Mastering Measures of Dispersion in Python: The Keys to Full Data Understanding
- Analyzing Class Performance: Range, Variance, and Standard Deviation Calculation in Python
- Analyzing Student Performance Scores: Switch to English Marks
- Unrevealed Measures of Dispersion
- Adding Measures of Dispersion to Student Score Analysis
- Calculating Measures of Dispersion for Math Scores
- Lesson 3: Exploring Quantiles and the Interquartile Range with Python
- Exploring Quartiles and Interquartile Range of Student Grades
- Calculating the Interquartile Range for Math Scores
- Fix the Interquartile Range Calculation
- Calculating the Interquartile Range of Math Scores
- Calculate Median and Interquartile Range of Student Grades
- Lesson 4: Mastering Statistical Computations with Scipy
- Analyzing Weather Patterns with Scipy
- Altering Parameters in the Weather Simulation
- Fix the Skewness and Kurtosis Calculation
- Compute Skewness and Kurtosis for Weather Data
- Analyzing Weather Patterns with Scipy
- Lesson 5: Unraveling the Mysteries of Data Distributions with Python
- Analyzing and Visualizing Normal Distribution with Python
- Exploring Normal Distribution in a Card Game
- Rectifying Normal Distribution Parameters for a Card Game
- Generating and Analyzing Uniform Distributions with Python
- Simulating and Analyzing Normal Distribution for Heights of Basketball Team Players
