Applied Statistics

Welcome

Overview

Course overview
Literature

Data and study design

Data Analysis in Python
First data analysis
Data basics
Study design
Case passwords

Exploratory data analysis

Data to Viz
EDA in Python
Catgeorical data
Numerical data
Effective communication

Linear Regression

Simple regression
Case study height
Multiple regression
Case study houses

Classification

Logistic regression

Foundations of inference

Hypothesis testing with randomization
CI with bootstrapping
Inference with mathematical models
Decision errors

Statistical inference

Single proportion
Two proportions
Two way tables
Single mean
Two means

Inferential modeling

Simple regression
Multiple regression

References

Bibliography

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Multiple regression

Multiple regression¶

Inference for linear regression with multiple predictors

Resources

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Reading: IMS 25

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Bibliography

By Jan Kirenz
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