General Information
- Target audience: Master’s and PhD students, researchers.
- Minimum number of registrations:Â 5
- Maximum number of registrations:Â 25
- Language:Â English
- Requirements:Â Basic knowledge of the R language
- Course participants will receive a certificate of attendance.
Registrations
Fee:
- CIIMAR/U.Porto/CCMAR members (attach proof): 100€
- External participants: 150€
- Register through this https://forms.office.com/e/XBpcB88Ftp
- Pay through bank transfer to CIIMAR Bank Details PT50007900000826888810276
- Send proof of payment required to book the place (to trainingandcareer@ciimar.up.pt ).
- After sending the proof of payment, a confirmatory e-mail for the registration will be sent.
Course description
This course will focus on four aspects: descriptive statistics, distributions, regression, and hypothesis testing.
Mastering these aspects will enable students to study in the future more complex statistical models that are more useful today in research, such as GLM and its extensions GLZ and GAM. In this course will be included an introductory example of GLM with an Analysis of Variance, that also includes random factors will be seen in an introductory way.
Although this course uses the R programming language as the basis for the examples and exercises, which will undoubtedly serve to further familiarize the student with it, learning this language is not an objective of this course.
Specific aims of the course
- Understand the meaning and usefulness of the main descriptive statistics parameters and measures.
- Learn basic aspects of distributions: parameters that define them, estimation of these parameters from a series of data, usefulness of the different distributions.
- Become familiar with different basic graphic exploration options.
- Learn to differentiate the common aspects that define all regression techniques, and also those that differentiate them to apply them to each specific case.
- Learn various ways of fitting and selecting regression models.
- Understand the objective and fundamentals of hypothesis testing, as well as provide a general view of all the specific cases that exist for these tests, both in the parametric and non-parametric statistical framework.
- Understand the fundamentals of the analysis of variance.
- Recognize the differences between fixed factors and random factors, in the context of the general linear model using analysis of variance.
Course Programme
Check the course’s programme here.
Find out more about this opportunity here.