Design-Statistical-Models

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Design-Statistical-Models

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Design Statistical Models on OpenClassrooms

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# Design-Statistical-Models
This repository, contains the Jupyter notebooks and datasets companions to the OpenClassrooms course: [Design Statistical Models](https://openclassrooms.com/en/courses/5873596-perform-effective-data-modeling)

## Part I

We start with the core concepts required to build linear regression models

* Linearity
* Correlation
* Hypothesis testing

## Part II

We move on to univariate and multivariate linear regression.
We start with hands-on applications  to standard datasets and follow up with the underlying theoretical basis.

* Univariate and multivariate linear regression
* The 5 assumptions of linear regression
* The mathematical basis for Linear regression

## Part III

We expand the framework of linear regression for classification, handling categorical variables and polynomial regression.

* Logistic regression
* Dealing with categorical variables
* Polynomial regression

## Part IV

In the last part we move from statistical modeling to a predictive analytics approach and address overfitting, cross validation and classification metrics.

* Predicting with linear regression
* Classification metrics and model selection

The datasets are available in the /data folder.

Design-Statistical-Models

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