Tech-Method Course:
From R to statistics
Date
17-20-21-22 April 2026
Organizer
Valeria Ranzani (INGM)
Location
INGM, Via F. Sforza 35 - Milan
About the Course
The course introduces students to R programming, data manipulation, visualization and bases of statistics. The main topics include R fundamentals, data structure, manipulation and data visualization with ggplot2. It also covers fundamentals of descriptive statistics and bases of statistical inference, including hypothesis testing, p-values, parametric vs. non-parametric tests and test selection. Practical sessions emphasize R scripting and handling data.
R fundamentals for data analysis
10.00-17.30
– Introduction and history of R
– IDEs, RStudio, packages and good practices
– Anatomy of a command, standard output/error, batch vs interactive mode
– R data structures, basic operators, objects and classes
– Reading data into R
– Tidy data
– Key R functions for working with tidy data
Data visualization with ggplot2
10.00-17.30
– Introductory principles of data visualisation
– The generic R: graphic devices, plot command, colors
– Colors in R
– The grammar of graphics
– The ggplot2 levels and hierarchy
– Different types of geoms for different types of data
(histograms, bar plots, pie charts, density plots, scatter plots, box plots)
– Piping summarized data into ggplot
– Special purpose graphics: volcano plots, heatmaps, bubble plots
Fundamentals of descriptive statistics
10.00-17.30
– Different kind of data, how to distinguish them
– Basic descriptive indices
– How to evaluate data position, variability and symmetry
– How to interpret data position, variability and symmetry
– Correlation and covariance
Bases of statistical inferences
10.00-17.30
– Research hypotheses and tests
– Definition of null and alternative hypothesis
– The p-value
– One and two-sided tests
– (optional) Type I and II errors and power of a test
– Evaluating performances: Sensitivity and Precision
– Differences between parametric and non-parametric tests
– Choosing the most fitting test to answer a question
– Differences between independent and paired tests
– How to choose a test