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https://github.com/dcs-training/r-visualisation-and-stats

This repository contains material from a 8 classes course on Data Visualisation and statistics with R
https://github.com/dcs-training/r-visualisation-and-stats

data-analysis data-visualisation data-wrangling intro-to-programming r statistics

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This repository contains material from a 8 classes course on Data Visualisation and statistics with R

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README 

        
# R-Visualisation-and-Stats

Readme File 



Hello Everyone! This is the Readme File for the **Statistics and Visualisation with R** Class. 



This course is focusing on 2 aspects of using R for your research i.e. **visualising your data** and **compute some basic Statistics** on it. 



There is much more you can do with R and R Studio and there are a lot of video tutorials you can watch and posts you can read: 



- If you want to learn more on **Data Wrangling** with R: [https://www.linkedin.com/learning/data-wrangling-in-r/welcome?u=50251009 ](https://www.linkedin.com/learning/data-wrangling-in-r/welcome?u=50251009)[https://datacarpentry.org/R-ecology-lesson/03-dplyr.html ](https://datacarpentry.org/R-ecology-lesson/03-dplyr.html)

- If you want to keep learn **small bits over a long period** of time this is a very interesting approach[ https://www.linkedin.com/learning/r-for-data-science- lunchbreak-lessons/exercise-files?u=50251009 ](https://www.linkedin.com/learning/r-for-data-science-lunchbreak-lessons/exercise-files?u=50251009)

- **Machine Learning** with R[ https://machinelearningmastery.com/machine- learning-in-r-step-by-step/ ](https://machinelearningmastery.com/machine-learning-in-r-step-by-step/)[https://www.datacamp.com/community/tutorials/machine-learning-in-r ](https://www.datacamp.com/community/tutorials/machine-learning-in-r)

- If you want to learn more on using **R and GIS together**  



[http://research.shca.ed.ac.uk/past-by-numbers/ ](http://research.shca.ed.ac.uk/past-by-numbers/)[https://www.jessesadler.com/post/gis-with-r-intro/ ](https://www.jessesadler.com/post/gis-with-r-intro/)

 



More generally, the good thing of R being an Open Source software means you can find  a lot of help online. If at any point of your research you get stuck on something just google the issue and 99% of times someone else posted about it already! 



The best sites on where to **find info and help** are: 



- [https://stackoverflow.com/ ](https://stackoverflow.com/)

- [https://www.r-bloggers.com/ ](https://www.r-bloggers.com/)



Finally if you want to **learn more about what R can do** you can find more info in here: 



- [https://www.r-project.org/about.html ](https://www.r-project.org/about.html)

- [https://blog.revolutionanalytics.com/2012/07/a-big-list-of-the-things-r-can-do.html ](https://blog.revolutionanalytics.com/2012/07/a-big-list-of-the-things-r-can-do.html)

- [https://simplystatistics.org/2019/03/13/10-things-r-can-do-that-might-surprise- you/ ](https://simplystatistics.org/2019/03/13/10-things-r-can-do-that-might-surprise-you/)



What you are going to find in this repo



- In  the  ***installation  instructions***  you  can  find  the  installation instructions.  

- In the ***classes*** folder you can find all the codes covered during the course. 

- In  the  ***challenges***  folder  you  can  find a series of challenges with correspondent solutions that you can use to test what you have learnt. 

- In the ***datasets*** you are going to find all information concerning the datasets used in the classes and challenges. 



How to set a R project  



- We are going to cover the subject during the first class but you can find more info on how to set a project in here[ https://support.rstudio.com/hc/en- us/articles/200526207-Using-Projects ](https://support.rstudio.com/hc/en-us/articles/200526207-Using-Projects)

- Or you can watch this video:[ https://www.youtube.com/watch?v=pyJMWlDptYw ](https://www.youtube.com/watch?v=pyJMWlDptYw)

- For this class you would need 5 subfolders : 

- Data 

- Code 

- Challenges 

- Solution  

- Graphs  



## **Topics**

- Class 1: *Intro to R and R Studio*

- Class 2: *Types of Data and Grammar of Graphics*

- Class 3: *Intro to Statisitcs and Descriptive Statistics*

- Class 4: *Boxplots and Graph Customisation*

- Class 5: *Data Collection Bias, Probability and Distributions*

- Class 6: *Null-Hypothesis Testing*

- Class 7: *Barplots and How to Clean Messy Datasets*

- Class 8: *PCA and Cluster Analysis*

- Class 9: *Correlation, Regression, Similarity and Difference Coefficients*



This repo has a [![License: CC BY-NC 4.0](https://licensebuttons.net/l/by-nc/4.0/80x15.png)](https://creativecommons.org/licenses/by-nc/4.0/) license