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Course Description
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Course Name
Data Analysis
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Host University
Universidad Autónoma de Barcelona
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Location
Barcelona, Spain
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Area of Study
Algebra, Engineering Science and Math, Mathematics
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Language Level
Taught In English
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Prerequisites
Basic knowledge of statistics and matrix algebra. Background in linear regression and R software is
useful but not required.
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Contact Hours
45 -
Recommended U.S. Semester Credits3
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Recommended U.S. Quarter Units4
Hours & Credits
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Overview
Objectives and Contextualisation
The main objective of this course is to learn about the tools to analyse and visualize data to communicate results and make informed recommendations. During the course, we will learn modern statistical methods for modelling data and prediction based on them. We will learn to analyse quantitative relationships among variables. The analysis and the visualization of data will be implemented through R software. The course will cover essential tools for the analysis of data collected across all areas of science and industry, and will concentrate on the application of statistical methods with lab illustrations.Competences
• Data analysis and visualization.
• Making sense of complex datasets.
• Linear regression modelling.
• Supervised or unsupervised statistical learning.
• Application of R software.
• Analytical skills and critical thinking.
• Communicating analytical results.
Learning Outcomes
1. Analyse complex datasets.
2. Present data through various graphs.
3. Define variables and analyse relationships among them.
4. Predict the future values of variables.
5. Implement classification and clustering analyses.
6. Use resampling methods.
7. Carry out dimension reduction and principal component analyses.
8. Implement analyses based on random forests and deep learning methods.
9. Use R software for various data analyses.