Online Course

This course will give you an overview of applied statistics, including confidence intervals, hypothesis tests, ANOVA, non-parametric methods, and regression. Both with a bit of theory and with plenty of examples from applied science. Next course, May 2025.

Introduction to Applied Statistics

This course is best suited for researchers in experimental biology. It will cover the main methods of
interval estimation, hypothesis tests for means, proportions, and quantiles, including non-parametric methods, sample size estimations, simple linear regression, contingency tables, one-way ANOVA, and bootstrapping for one mean.

The emphasis will be on the applied side, with illustrative exercises and discussion of the methods, without entering into the details of their mathematical justification. The theoretical part will be explained by means of examples and intuitive arguments. The examples will be designed so that you can reproduce the results using your own reference software.

During the course, you will have the chance to apply your knowledge to simple direct calculations that can be performed with your preferred software or even any spreadsheet calculator. If you are not interested in doing the exercises yourself, you can follow the live lecture, where I explain all steps involved. There, I will give you time to think about the problems discussed in the class. Participants will receive a copy of the lecture notes and a certificate of participation. Participants affine to Python will get access to the Jupyter Notebooks with all calculations.

The course will not dwell on descriptive statistics and data visualization, even though these topics can be discussed during the class if needed. If you are interested in data visualization and description, you can take the one-day free course on this topic. This course is not suited to people who have already a clear knowledge of the topics covered by the course, as listed above. The course will also not make use of one specific software, nor it will cover the functionality of any software in general. If you are interested in applying your knowledge to the live exercises, you can choose the software that you prefer, or you are accustomed to using. If you are not sure about which software to use, you are welcome to contact me before the start of the course.

Duration:
This course will be five hours per day for three days (total of 15 hours), plus several short breaks, a lunch break, and time for questions.

Dates:
2025, May (dates still to be decided)

Schedule:
The course starts at 9am and ends at 4pm. Lunch break will be at around 12:30pm.

Price:
400 EUR per single participant (registering a group? Send an email for an offer)

Format:
Online, registered participants will receive a link to the lectures. The lectures won’t be recorded.

Bonus materials:
All Jupyter Notebooks, all datasets, and a full set of useful functions in Python to be freely used.

Pre-requisite:
High-school level of algebra and calculus.

Registration: Please register for the newsletter. A dedicated email address will be used to register for the course when registration is open.

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Angelo Valleriani

Theoretical physicist turned into a multidisciplinary scientist

I’ve been inspired by a diverse range of topics like malaria, cancer, and gene expression, applying this knowledge in my teachings. My teaching now focuses on applied statistics, where I blend theory and experiment to elucidate the math behind randomness. Despite my affinity for the mathematical details, I understand the importance of intuition in teaching. On this website, I offer courses designed for those who are curious or preparing for a professional course, aiming to make complex statistical theories accessible to all.

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