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Python Statistics Essential Training

via LinkedIn Learning

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Overview

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Learn to use Python to unlock the power of data and use it to inform decisions.

Syllabus

Introduction

Being a Python statistics MVP
What you should know
Using GitHub Codespaces with this course

1. Loading and Cleaning Data

Loading data
Strings and categories
Cleaning numbers
Shrinking numbers
Challenge: Clean Ames
Solution: Clean Ames

2. Exploring and Visualizing

Categorical exploration
Histograms and distributions
Outliers and Z-scores
Correlations
Scatter plots
Visualizing categorical and numerical values
Comparing two categoricals
Challenge: Explore Ames
Solution: Explore Ames

3. Linear Regressions

Linear regression
Interpreting linear regression models
Standardizing values
Regression with XGBoost
Challenge: Predict Ames
Solution: Predict Ames

4. Hypothesis Tests

Exploring data
Visualizing distributions
Running statistical tests
Testing for normality
Challenge: Checking square footage distributions
Solution: Checking square footage distributions

Conclusion

Next steps

Taught by

Michele Vallisneri

Reviews

4.7 rating at LinkedIn Learning based on 137 ratings

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