Statistics for Data Analysis Using Python

Unlock the power of statistics and data analysis with Python! No prior programming experience needed – this course is designed for everyone. We'll start with the fundamentals, building your skills step-by-step. Coding exercises reinforce your learning, ensuring you can confidently apply statistical methods.

This course goes beyond just coding; we'll also explore the underlying statistical principles using traditional methods (like a calculator from the 1960s!), giving you a deep understanding of the tests. Learn to apply statistics in your workplace and make data-driven decisions.

You'll gain a solid understanding of core statistical concepts and learn how to implement them using Python. We'll use real-world examples and datasets to illustrate practical applications. We'll cover the theory first, then demonstrate the Python implementation.

Here's a detailed look at the statistical topics we'll cover:

• Descriptive Statistics: Master essential measures like mean, mode, median, quartile, range, and interquartile range, along with standard deviation.
• Data Visualization: Create insightful visualizations using Matplotlib.pyplot and Seaborn libraries. Learn to generate effective histograms, box plots, and scatter plots.
• Probability: Grasp fundamental probability concepts, including permutations and combinations.
• Population and Sampling: Understand the difference between population and sampling and their implications.
• Probability Distributions: Explore common probability distributions such as Normal, Binomial, and Poisson.
• Hypothesis Testing: Perform hypothesis testing with both one-sample and two-sample tests. We'll cover the z-test, t-test, F-test, and Chi-Square test.
• ANOVA: Learn Analysis of Variance (ANOVA) – perform it step-by-step using manual calculations and Python.
• Goodness of Fit & Contingency Tables: Analyze data using Goodness of Fit tests and interpret contingency tables.

By the end of this course, you'll be able to confidently perform statistical calculations and data analysis using Python, empowering you to extract valuable insights from your data.