This page provides an overview on all entries that relate explicitly to statistical analyses.
New to statistics?
These are some basic entries on statistics that you should read when you start your statistics journey:
- ANOVA - a statistical method that allows to test differences of the mean values of groups within a sample.
- Introduction to statistical figures - an overview page for all kinds of data visualisation.
- Data formats - explains all different kinds of data types.
- Data distribution - what is a normal distribution, and how can you identify it?
- Correlations - Correlations are a basic method in statistics that you should know about.
- Regression Analysis - Regressions are Correlations + Causality and let you predict data.
- Experiments - an overview on the history and different kinds of experiments.
- Why statistics matters - why should you engage with statistics?
- Bias in statistics - statistics can be flawed, and we tell you why.
How to find the right statistics method
Often, you know which kind of data you want to analyze, but there are so many options how to do it, and you don't know how to start.
Do not worry. The following interactive page asks you simple questions about your data and guides you to the best statistical analysis method for your research.
An initial path towards statistical analysis
How to code in R
On this Wiki, we believe in the importance of experience, and therefore provide guidance on how to approach statistical analyses in the Software R.
The following list includes all Wiki entries that include R code examples: All R example pages
All statistics entries
There is a lot more than the aforementioned entries. Some revolve around statistical methods, others around the normativity of statistics.
The following list includes all Wiki entries on Statistics: All statistics entries