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Technical Courses I: Methodological approaches in Neuroscience, Statistics (SPSS, R programming, graphpad)


This sub-course is indented to cover the basic statistical principles usually applied in the biological sciences. The goal of the course is to provide the students with the ability to choose and apply the appropriate statistics for their studies.

Course Overview

The course will begin with an analysis of the hypothesis test, a statistical test used to compare two data sets for the purpose of rejecting a null hypothesis and not to indicate the more likely of two hypotheses. The students will also be introduced in the process of randomization, of making something random, for example on how to select a random sample of a population. In addition, the course will provide detailed information on some of the most commonly used distributions and an analysis of the central limit theorem which establishes that the sum of independent random variables tends toward a normal distribution although the original variables may not. Time will be allocated in the presentation of parametric and nonparametric tests and their comparison in order for the students to understand the prerequisites for applying one or the other. Special attention will be given to the multiple comparison problems and means to overcome it. The problem arises from the fact that when you are performing multiple statistical tests a fraction of them is false positives. The application of Linear, Logistic and Cox models will be also presented.