Course: Data Science 2 credits: 5

Course code
BFVM23DATASCNC2
Name
Data Science 2
Study year
2023-2024
ECTS credits
5
Language
Dutch, with parts in English
Coordinator
F. Feenstra
Modes of delivery
  • Lecture
Assessments
  • Bayesian Statistics - Computer, organised by School
  • Numerical Analysis - Computer, organised by School

Learning outcomes

  • You assess the quality- of- life science data and perform data clean-up  

  • You apply frequentist and Bayesian methods to estimate parameters with standard errors and confidence intervals  

  • You implement and apply numerical methods for analysis of data, including differentiation, integration and finding roots and extrema  

  • You explain how discretization, round-off and error propagation may affect the results of outcomes 

Content

This course is designed to provide students with the practical implementation of numerical analysis and Bayesian statisticsStatistics and Numerical Analysis using Python.  

 

The first subject, Bayesian statisticsStatistics, covers topics such as constructing histograms, calculating sample moments, estimating parameters using the Method of Moment and Maximum Likelihood methods, evaluating various distributions, using null hypothesis significance tests, assessing normality, calculating standard errors and confidence intervals, and interpreting effect sizes. studentsStudents will learn how to use Bayes' theorem/law to calculate conditional probabilities and evaluate Bayesian estimators for parameters of various distributions using conjugated priors.  

 

The second subject, numerical analysisNumerical Analysis, is focused on the application of numerical methods to solve mathematical problems. The course will provide an overview of numerical differentiation, numerical integration, root finding, optimization, error propagation, and differential equations, and characterize their propagated errors. 

 

By the end of the course, students will have an understanding of numerical analysis and Bayesian statisticsStatistics and Numerical Analysis, and the ability to apply these concepts in their research 

Included in programme(s)

School(s)

  • Institute for Life Science & Technology
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