# Welcome to the 'Introduction to Data Analysis' course

The course material is accessible via the menu on the left.

This is a basic course aimed at scientists who want to make a start with data analysis. We will start with an introduction to R and provide a protocol for data exploration to avoid common statistical problems, discuss how to detect outliers, deal with collinearity and discuss transformations. An important tool used in statistics is linear regression. Various basic linear regression topics will be explained from a biological point of view. We will also discuss how many samples to take based on simulation
studies and power analysis. During the course several case studies are presented, in which the statistical theory is integrated with applied analyses in a clear and understandable manner.

#### Keywords

Simple data analysis. Outliers. Transformations. Collinearity (correlation between covariates). Linear regression. One-way anova. Two-way anova. Visualizing results. How many samples to take. Simulation study. Introduction to R.

#### Schedule

Monday & Tuesday

• Introduction to R.
• Data visualisation (spatial maps, time series plots, accessing Google map)
• Data exploration (outliers, collinearity, transformations, relationships, interactions).
• Exercises.

Tuesday - Thursday

• Introduction to linear regression models (including 1-way anova, 2-way anova, model selection, interactions,
sketching model fits).
• Making a variogram to assess spatial dependency.
• Making an auto-correlation function to assess temporal dependency.
• Exercises.

Friday

• Catching up.
• Learning how to program a loop in R.
• Simulation study and power analysis to investigate how many samples to take.
• Simulation study to investigate see how to sample a covariate.
• What to present in a scientific paper or thesis.
• Exercises

#### Pre-required knowledge

Basic statistics (e.g. mean, variance, histogram, normality). We assume no R knowledge.You will learn R on the fly. This is a non-technical course. You need to bring your own laptop.