Analysis of Variance
Objectives
Understand, develop and analyse the results of a designed experiment using R.
General characterization
Code
200205
Credits
4.0
Responsible teacher
Carolina Micael de Abreu e Vasconcelos
Hours
Weekly - Available soon
Total - Available soon
Teaching language
Portuguese. If there are Erasmus students, classes will be taught in English
Prerequisites
Matrix algebra and statistics (recommended)
Bibliography
Teaching method
The theoretical classes aim to provide the student with the theoretical background for each topic.
The practical classes aim to apply the concepts and methodologies learned in the theoretical classes.
Evaluation method
The final grade depends on the project grade (PG) throughout the semester and the final exam (FE) (first and second season).
FG = max{0.4PG + 0.6FE; FE}
The formula above implies the following: if the final exam grade is higher than the project grade, the final grade is given exclusively by the final exam grade. If not, the final grade is given by the formula 0.4PG + 0.6FE.
Subject matter
1. Principles of Experimental Design and Simple Comparative Experiments
2. Experiments with a Single Factor: The Analysis of Variance
3. Blocking
4. Factorial Design
Programs
Programs where the course is taught:
- Specialization in Risk Analysis and Management
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- Master Degree in Data Driven Marketing
- Specialization in Digital Marketing and Analytics
- Specialization in Digital Marketing and Analytics
- Specialization in Marketing Intelligence
- Laboral - Data Science for Marketing
- PostGraduate in Data Analysis
- PostGraduate Risk Analysis and Management
- PostGraduate in Data Science for Marketing
- PostGraduate in Enterprise Information Systems
- Postgraduate Program in Statistical Systems with a specialization in Official Statistics