Read about our experience with Coding Club and check out our tutorials. Each tutorial post includes instructions and a link to the Github repository from where you can download all files necessary to participate in our workshops remotely.

Introduction to ordination

04 May 2018

Tutorial Aims 1. Get familiar with ordination 2. Learn about the different ordination techniques 3. Interpret ordination results In this tutorial, we will learn to use ordination to explore patterns in multivariate ecological datasets. We will mainly use the vegan package to introduce you to three (unconstrained) ordination techniques: Principal...

Generalised linear models in Stan

30 April 2018

Tutorial Aims: 1. Learn about generalised models in Stan 2. Use the rstanarm package to run a Poisson model 3. Assess model convergence 4. Check priors in rstanarm 5. Extract Stan code 6. Run a model with a negative binomial distribution 7. Compare rstanarm and brms All the files you...

Python Data Analysis with Pandas and Matplotlib

18 April 2018

Welcome to this tutorial about data analysis with Python and the Pandas library. If you did the Introduction to Python tutorial, you’ll rememember we briefly looked at the pandas package as a way of quickly loading a .csv file to extract some data. This tutorial looks at pandas and the...

Intro to Stan

17 April 2018

Tutorial Aims: 1. Learn about Stan 2. Prepare a dataset for modelling 3. Write a programme in Stan 4. Run a Stan programme 5. Specify priors in Stan 6. Assess convergence diagnostics All the files you need to complete this tutorial can be downloaded from this repository. Click on Clone/Download/Download...

Intro to model design

06 April 2018

Tutorial Aims: 1. Learn what is a statistical model 2. Come up with a research question 3. Think about our data 4. Think about our experimental design 5. Turn a question in to a model 6. Learn about the different types of models 7. General linear models 7. Hierarchical models...

GitHub, Tidyverse and Markdown - a coding workshop for the EVENET network

06 March 2018

Tutorial Aims: 1. Create a coding tutorial and host it on GitHub 2. Set up version control with GitHub and RStudio 3. Analyse and visualise data using the tidyverse 4. Create a reproducible report using Markdown All the files you need to complete this tutorial can be downloaded from this...

Analysing ordinal data, surveys, count data

29 January 2018

Tutorial Aims: 1. Learn how to format survey data, coding responses, data types etc. 2. Practise visualising ordinal data, count data, likert scales 3. Mining text responses and comments for keywords. 4. Statistically analyse qualitative data This workshop will explore qualitative data, the sort of data you might collect through...

Intro to Python

26 January 2018

Tutorial aims: Understand why Python is so useful for scientific programming 1. Installing Python and running a simple Python program 2. Reading data from a file 3. Get a feel for how Python looks and feels 4. Load data from a text file into memory 5. Learn about some basic...

Meta-analysis for biologists using MCMCglmm

22 January 2018

This tutorial is aimed at people who are new to meta-analysis and using MCMCglmm, to help you become comfortable with using the package, and learn some of the ways you can analyse your data. It isn’t designed to teach you about hardcore Bayesian statistics or mixed modelling, but rather to...

Manipulation and visualisation of spatial and population data

06 January 2018

Tutorial Aims: 1. Download, format and manipulate biodiversity data 2. Clean species occurrence data 3. Visualise & customise species occurrence and population trends All the files you need to complete this tutorial can be downloaded from this repository. Click on Clone/Download/Download ZIP and unzip the folder, or clone the repository...

Transferring quantitative skills among scientists

23 November 2017

Tutorial Aims: 1. Get familiar with the Coding Club model 2. Write your own tutorial 3. Publish your tutorial on Github Key steps Each step is explained in detail as you start going through the workshop resources below. Have a quick read. There is no need to click on links...

Quantifying and visualising population trends

11 November 2017

Tutorial Aims: 1. Tidy dataset 2. Calculate population change 3. Make a map of vertebrate population change in Europe All the files needed to complete this tutorial can be downloaded from this Github repository. Click on Clone or Download/Download ZIP and then unzip the files. In this tutorial we will...

Coding Club is back for the new academic year!

14 September 2017

Coding Club is almost a year old! Time has flown by, many lines of code have rolled in, and we have gathered quite the collection of tutorials on our website! It has been so wonderful to meet people keen to advance their quantitative skills and learn more about coding! It’s...

Coding Club goes to Aberdeen and SEECC 2017!

13 September 2017

It’s been almost a year since we first started pondering the idea of a positive and supportive environment where we can all advance our skills in statistics and programming. We had a vision for a place where we can learn without the pressure of formal assessment, and with the ability...

Setting up a GitHub repository for your lab

15 May 2017

Tutorial Aims: 1. Set up a lab GitHub organisational account 2. Organise your lab repository 3. Develop a coding & GitHub etiquette 4. Learn to use RStudio and Github together What is version control? Version control allows you to keep track of your work and helps you to easily explore...

Analysing Time Series Data

26 April 2017

Tutorial Aims: 1. Formatting time series data 2. Visualising time series data 3. Statistically analysing time series data 4. Challenge yourself with new data In this tutorial, we will consider how to explore and analyse time series data in R. Time series analysis is a powerful technique that can be...

Coding etiquette

25 April 2017

Tutorial Aims: 1. Organising scripts into sections 2. Following a coding syntax etiquette 3. Tidying up old scripts and data frames When analysing data in R, the lines of code can quickly pile up: hundreds of lines to scroll through, numerous objects whose names might make sense to you, but...

Data visualisation 2

29 March 2017

Tutorial Aims: 1. Create and customise figures in ggplot2 2. Plot results from mixed effects models Following from our first tutorial on intro to data visualisation using ggplot2, we are now back for more ggplot2 practice and customisation. The ultimate aim of this tutorial is to help you to make...

Intro to data clustering

21 March 2017

Tutorial Aims: 1. Get acquainted with data clustering 2. Learn about different distance metrics 3. Learn about different linkage methods 4. Turn groups into a grouping variable 5. Map cluster groups in geographic space To get all you need for this session, go to the repository for this tutorial, fork...

Working efficiently with large datasets

20 March 2017

Tutorial Aims: 1. Formatting and tidying data using tidyr 2. Efficiently manipulating data using dplyr 3. Automating data manipulation using lapply(), loops and pipes 4. Automating data visualisation using ggplot2 and dplyr 5. Species occurrence maps based on GBIF and Flickr data Quantifying population change This workshop will provide an...

Introduction to linear mixed models

15 March 2017

This is a workshop is aimed at people new to mixed modeling and as such it doesn’t cover all the nuances of mixed models, but hopefully serves as a starting point when it comes to both the concepts and the code syntax in R. There are no equations used to...

Getting Started with Shiny

07 March 2017

Tutorial aims: 1. Downloading Shiny 2. Getting familiar with the Shiny app file structure 3. Getting familiar with the Shiny app.R layout 4. Creating a Shiny app 5. Exporting a finished app 6. Challenge yourself to write an app At it’s core, Shiny is merely an R package like dplyr...

Web Scraping

06 March 2017

Tutorial Aims: 1. Isolate and retrieve data from a html web page 2. Automate the download of multiple web pages using R 3. Understand how web scraping can speed up the harvesting of online data Steps: 1. Download the relevant packages 2. Download a .html web page 3. Import a...

From distributions to linear models

28 February 2017

Tutorial Aims: 1. Get familiar with different data distributions 2. Practice linear models 3. Practice generalised linear models Are your data all nicely formatted and ready for analysis? You can check out our Data formatting and manipulation tutorial if tidying up your data is still ahead of you, but if...

Intro to Github for version control

27 February 2017

Tutorial Aims: 1. Get familiar with version control 2. Learn to use RStudio and Github together 3. Create your own repository and sync through RStudio What is version control? Version control allows you to keep track of your work and helps you to easily explore the changes you have made,...

Intro to loops and functions

08 February 2017

Tutorial Aims: 1. Learn to write functions to code more efficiently 2. Learn to write loops to make multiple graphs at once Note: all the files you need to complete this tutorial can be downloaded from this repository. Writing functions We’ve learned how to import our data in RStudio, format...

Beautiful and informative data visualisation

29 January 2017

Tutorial Aims: 1. Get familiar with the ggplot2 syntax 2. Practice making different plots with ggplot2 3. Learn to arrange graphs in a panel and to save files Note : all the files you need to complete this tutorial can be downloaded from this repository. Clone and download the repo...

Easy and efficient data manipulation

16 January 2017

Tutorial Aims: 1. Understand the format required for analyses in R, and how to achieve it 2. Use efficient tools for manipulating your data 3. Learn a new syntax for coding: pipes Note : all the files you need to complete this tutorial can be downloaded from this repository. Clone...

Coding club progress and future plans

03 January 2017

We are all thrilled to have launched Coding Club at the end of 2016 and are very excited to see it grow in 2017. Coding Club is a peer-to-peer learning community aiming to develop quantitative skills, in particular fluency in statistics and programming. We are working as a team of...

Spatial Data and Maps

11 December 2016

Tutorial Aims: 1. Learn to download map tiles using ggmap 2. Make a simple map using ggmap 3. Import, manipulate and plot shapefiles Steps: 1. Why use R to make maps? 2. Downloading the relevant packages 3. Getting your head around map data 4. Creating a map using ggplot2 and...

Getting Started with R Markdown

24 November 2016

Tutorial Aims: 1. Understand what RMarkdown is and why you should use it 2. Learn how to construct an RMarkdown file 3. Export an RMarkdown file into many file formats Steps: 1. What is RMarkdown? 2. Download RMarkdown 3. Create an RMarkdown (.Rmd) file 4. Identify the different parts of...

Troubleshooting and how to find help

15 November 2016

Tutorial aims: 1. Learn how to pick up on errors in R 2. Get familiar with common errors and solutions 3. Learn how to find help online 4. Practice by fixing errors in an example script In our first tutorial we learned how to import data into RStudio, conduct a...

Getting started with R and RStudio

13 November 2016

Tutorial aims: 1. Learn how to import data 2. Learn how to create vectors and data frames 3. Make a simple plot Steps: 1. Download R and RStudio 2. Import and check data 3. Calculate species richness 4. Create a vector and plot it 5. Create a data frame and...

Preparing to launch Coding Club

17 October 2016

Over the summer, we have been preparing to launch Coding Club - lots of excitement and a long to do list! We are all looking forward to Coding Club - our vision of a supportive peer-to-peer learning community becoming a reality! We have been working on grant applications, this website...

Advanced data manipulation and visualisation

06 March 2016

Tutorial Aims: 1. Create a reproducible report using Markdown 2. Learn about the tidyverse 3. Use pipes to make figures with large datasets 4. Download and map data from large datasets ** General bit about this being a BES QE SIG event** All the files you need to complete this...