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Statistics Fundamentals in Python

Confidently learn to calculate statistics and probability, evaluate statistical models, and draw conclusions from hypothesis tests.
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Track Description

Statistics Fundamentals in Python

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!

Prerequisites

There are no prerequisites for this track

  • Course

    1

    Introduction to Statistics in Python

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

  • Course

    4

    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.

  • Course

    5

    Hypothesis Testing in Python

    Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

  • Project

    bonus

    Hypothesis Testing with Men's and Women's Soccer Matches

    Perform a hypothesis test to determine if more goals are scored in women's soccer matches than men's!

Statistics Fundamentals in Python
5 courses
Track
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