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Material & code for a course in statistical analysis with R

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Introduction to statistical methods with R
================
This repository contains teaching material for **introductory** courses of statistics in R.

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Courses
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We provide the Github markdown below, but the rendering is much better in html notebook. The latter can be found  [[here]](https://www.gcoqueret.com/rstats.html).

1.  [**Introduction to the tidyverse**](https://github.com/shokru/rstats/blob/master/pages/S1_tidyverse.md): plotting, filtering, organising data.

2.   [**Basic R instructions**](https://github.com/shokru/rstats/blob/master/pages/S2_Basics.md): package installation, data generation, matrix & dataframe manipulation, loops and simple functions.

3.   [**Distributions**](https://github.com/shokru/rstats/blob/master/pages/S3_Distributions.md): descriptive statistics, parametric distributions, plots, histograms, etc.

4.   [**Maximum likelihood estimation**](https://github.com/shokru/rstats/blob/master/pages/S4_MLE.md): moment matching versus the mle/mle2 functions.

5.   [**Monte-Carlo simulations**](https://github.com/shokru/rstats/blob/master/pages/S5_MC.md): random number generation with sequential tournaments as examples + cool exercises.

6.   [**Time-series analysis**](https://github.com/shokru/rstats/blob/master/pages/S6_TS.md): AR, VAR fitting & predictions using **[French economic data](https://github.com/shokru/rstats/blob/master/data/economics.RData)**.

7.   [**Bayesian inference**](https://github.com/shokru/rstats/blob/master/pages/S7_Bayes.md): conjugate priors, grid approximation and a snapshot of Markov Chains (but no MCMC sadly).

8.   [**Statistical tests & regressions**](https://github.com/shokru/rstats/blob/master/pages/S8_Test.md): one and two mean tests, basic regression analysis.

Supplementary material:
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The original **[Rmd files](https://github.com/shokru/rstats/blob/master/material/all_Rmd.zip)** (.zip) as well as the correction of exercises: **[data + html and Rmd format](https://github.com/shokru/rstats/blob/master/material/Solution_files.zip)** (.zip also).

[**R memo**](https://github.com/shokru/rstats/blob/master/pages/R_Memo.md) : a compilation of everything you need to know (survival toolkit).

[**Example on financial data**](https://github.com/shokru/rstats/blob/master/pages/Fin_solutions.md): exercises on 30 large US firms; data **[here](https://github.com/shokru/rstats/blob/master/data/data.RData)**.
 
 [**Short tutorial**](https://gcoqueret.shinyapps.io/Tidyverse-exercises/): online exercises (& solutions) on the core functions of the tidyverse.

**Links:** [R on the web](https://github.com/shokru/rstats/blob/master/material/R_links.md): a short list of links, sorted by themes.

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Datasets:
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> **[ANES data: US political surveys (1990-2016)](https://github.com/shokru/rstats/blob/master/data/anes.RData)** and in **[Excel form](https://github.com/shokru/rstats/blob/master/data/anes.xlsx)**

> **[French economic indicators](https://github.com/shokru/rstats/blob/master/data/economics.RData)**

> **[Financial data on 30 large US firms](https://github.com/shokru/rstats/blob/master/data/data.RData)**

You can download all files at once **[here](https://github.com/shokru/rstats/blob/master/data/all_files.zip)**.

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**DISCLAIMER**: the data and code are meant for pedagogical use only.

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