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://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
- Machine Learning with R https://machinelearningmastery.com/machine- learning-in-r-step-by-step/ 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/ 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:
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://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/
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
- Or you can watch this video: https://www.youtube.com/watch?v=pyJMWlDptYw
- For this class you would need 5 subfolders :
- Data
- Code
- Challenges
- Solution
- Graphs
- 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 