Statistics Fundamentals in Python

Overview

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Statistical knowledge is key to evaluating, interpreting, and reporting findings from your data. In this skill track, you'll learn the four fundamentals of statistics using Python, including: ✓ Summary statistics and probability ✓ Statistical models such as linear and logistic regression ✓ Techniques for sampling ✓ How to perform hypothesis tests and draw conclusions from a wide variety of data sets By the end of this track, you'll be ready to apply your statistical skills in Python to analyze data, implement and evaluate statistical models, and draw conclusions from hypothesis test results!

Syllabus

Introduction to Statistics in Python

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.

Introduction to Regression with statsmodels in Python

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis with statsmodels in Python.

Intermediate Regression with statsmodels in Python

Learn to perform linear and logistic regression with multiple explanatory variables.

Sampling in Python

Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.