Objectives of Programme's Learning Outcomes

• Master expertise.
• Have developed the knowledge and skills acquired in the previous cycle to a level that extends beyond the Bachelor's course in Physics, and which provides the basis for the development and implementation of original ideas in a professional context.
• Provide clear and accurate information.
• Share their knowledge and findings clearly and back them up rationally to specialist and non-specialist audiences.
• Have a creative and rigorous scientific approach
• Gather and interpret relevant scientific data and critically analyse it, distinguising working hypotheses of proven facts.
• Apply their knowledge, understanding and ability to solve problems in new or unfamiliar environments and in multidisciplinary contexts related to physical sciences.
• Master expertise.
• Have developed the knowledge and skills acquired in the previous cycle to a level that extends beyond the Bachelor's course in Physics, and which provides the basis for the development and implementation of original ideas in a professional context.
• Provide clear and accurate information.
• Share their knowledge and findings clearly and back them up rationally to specialist and non-specialist audiences.
• Grow personally and professionally.
• Have developed the skills that will enable them to continue to acquire knowledge independently.
• Have a creative and rigorous scientific approach
• Gather and interpret relevant scientific data and critically analyse it, distinguishing working hypotheses of proven facts.
• Apply their knowledge, understanding and ability to solve problems in new or unfamiliar environments and in multidisciplinary contexts related to physical sciences.

Learning Outcomes of UE

At the end of the instruction, the students will be able to :
- Identify the multivariate analysis technique according to the nature of the statistical variables
- to apply the techniques of analysis in principal components, analysis of the (multiple) correspondences and the automatic classification in the statistical treatment of multidimensional sets of data
- to use a software of multidimensional statistical analysis

Content of UE

- Singular values decomposition
- Principal components analysis
- (Multiple) correspondence analysis
- Techniques of classification (k-means, hierachical clustering)
- Support vector machines

Prior Experience

- Uni- and bivariate basic statistics
- Hypothesis tests
- Basic matrix algebra
 

Type of Assessment for UE in Q1

• N/A

Q1 UE Assessment Comments

Not applicable

Type of Assessment for UE in Q2

• Presentation and works

Q2 UE Assessment Comments

Not applicable

Type of Assessment for UE in Q3

• Oral examination

Q3 UE Assessment Comments

Not applicable

Type of Resit Assessment for UE in Q1 (BAB1)

• N/A

Q1 UE Resit Assessment Comments (BAB1)

Not applicable