Statistical Tools
Blas MOLA-YUDEGO
Main Statistical Tools
What are statistical tests? Why are tests useful? How can we choose the proper test? The main purpose of statistical testing is to make decisions about our data. To accept or reject hypotheses. We use statistical tests to differentiate variation in our data due to a reason (i. e. a treatment) or due to noise. There are different types of statistical tests. In this part of the course we will learn how to choose the appropriate test in each case and how to apply them to make decisions about our data. We will learn about: one-sample t-test, independent samples t-test, paired samples t-test, and one-way ANOVA. During the lectures, we will practice how to apply these tests through exercises. Those exercises consist in analyzing the outcome of the explained tests in different study cases.
Objectives
- To understand how tests can help us to infer data of the population from our sample.
- To learn how can we simplify a problem using hypotheses.
- To differentiate various types of statistical tests and when to apply each one of them.
- To be able to interpret the results of a statistical test.
Topics
Measuring uncertainty. Blas Mola (2025) [PDF]. Precision as evidence. Standard error quantifies how much an estimate would vary across repeated samples, turning uncertainty into a number that guides inference and decision. It serves a scientific culture that balances tradition, careful design and probability, with innovation, resampling and robust methods, so claims are calibrated rather than absolute.
Tasks
Watch the videos and download the exercises related to the lectures. Check the practical exercises and try to solve them before the lectures. We will correct them together during the lectures.
How can you simplify the problem?
Do you know when to apply a statistical test?
How can you choose the appropriate test for your problem?