Miscellaneous
Environmental Computing
Welcome
About This Site
Basics
1
Installing R and RStudio
2
Basic Project Management
Data Literacy
3
Making Analysis Ready Data
4
Importing Data
5
Subsetting Data
6
Making New Variables
7
Combining Datasets
8
Summarising Data
9
Reshaping Data
Data Visualisation
10
Plotting in R
11
Multipanel Figures with ggplot2
12
Raster
13
Simple Maps with ggmap
14
Principal Component Analysis
15
Heatmaps
Statistical Methods
16
Linear Models
17
Linear Regression
18
Interpreting Linear Regressions
19
T-tests
20
ANOVA
21
Understanding Interactions
22
Generalised Linear Models
23
Interpreting GLMs
24
Mixed Effects Models
25
Generalised Additive Models (GAMs)
26
Time Series Forecast
27
Multivariate Analysis with mvabund
28
Cluster Analysis
29
Multidimensional Scaling
30
Meta Analysis
Coding Skills
31
Good Practices for Code
32
Writing Functions
33
Using Loops
34
Version Control
35
Asking Code Questions
Miscellaneous
36
Data Entry
37
Data Types + Structure
38
Using R Notebooks
39
Interactive Maps in R
40
Contingency Tables
41
Fisher’s Exact Test
42
Goodness of Fit
43
Power Analyses
Contributing to Environmental Computing
Appendices
A
Datasets
Miscellaneous
Some commonly used tests for contrasting the counts of observations across categorical variables.
Goodness of fit tests
Contingency tables
35
Asking Code Questions
36
Data Entry