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  4. Data Analysis and Probability

Data Analysis and Probability

Objectives

The course provides students with essential tools for the analysis of different data types and basic knowledge of probability theory and random variables. Students will use both computational and graphical methods to analyze the necessary information that will enable decision-making in Economics and Management.

General characterization

Code

1312

Credits

7

Responsible teacher

Ernesto Freitas | Patrícia Ferreira Ramos | Maria João Braga

Hours

Weekly - Available soon

Total - Available soon

Teaching language

Portuguese and English

Prerequisites


Bibliography

Newbold, P., Carlson, W. and Thorne, B. Statistics for Economics and Management: Global Edition. Pearson, 2013. ISBN: 9780273767090

Teaching method

Blended learning


Evaluation method

Regular Exam Period

«Continuous assessment elements (and their weights): midterm 1 (15%), midterm 2 (15%), group project (15%), weekly quizzes (5%) and class participation (5%)

«Final exam (and their weighting): final exam (45% or 60%) with a minimum score of 8.0 points. The final grade is the best of two possible scenarios:

A. Weighted average of all the assessment elements: 0.15*midterm 1 + 0.15*midterm 2 + 0.15*group project + 0.05*quizzes + 0.05*class participation + 0.45*final exam

B. Weighted average considering only the best midterm: 0.15*maximum(midterm 1, midterm 2) + 0.15*group project + 0.05*quizzes + 0.05*class participation + 0.6*final exam

Note: students who submitted the project in the previous three semesters may reuse their grade, students should file a request in the beginning of the semester and wait for approval.

Resit Exam Period (not applicable to Master courses)

«Continuous assessment (and their weights) if different than 100%: midterm 1 (15%), midterm 2 (15%), group project (15%), weekly quizzes (5%) and class participation (5%)

«Final exam (and its weighting): final exam (45% or 60%) with a minimum score of 8.0 points. The final grade is the best of two possible scenarios:

A. Weighted average of all the assessment elements: 0.15*midterm 1 + 0.15*midterm 2 + 0.15*group project + 0.05*quizzes + 0.05*class participation + 0.45*final exam

B. Weighted average considering only the best midterm: 0.15*maximum(midterm 1, midterm 2) + 0.15*group project + 0.05*quizzes + 0.05*class participation + 0.6*final exam

OR

Final exam (and its weighting): final exam (100%)

Grade Improvement in Regular Period (not applicable to Master courses)

«Continuous assessment (and their weights) if the scanning feature doesn't count 100%: same as the regular exam period

«Final exam (and its weight): same as the regular exam period Grade Improvement in Resit Period (not applicable to Master courses)

«Continuous assessment (and their weights) if different than 100%: same as the regular exam period «Final exam (and their weighting): same as the regular exam period) 


Subject matter

1: Descriptive Statistics – frequency distribution
2: Descriptive Statistics – numerical measures
3: Simple linear regression
4: Time series
5: Probability
6: Discrete probability distributions
7: Continuous probability distributions