Modern high throughput technologies easily generate data on thousands of variables; e.g. health care data, genomics, chemometrics, environmental monitoring, web logs, movie ratings, … Conventional statistical methods are no longer suited for effectively analysing such high-dimensional data. Multivariate statistical methods may be used, but for often the dimensionality of the data set is much larger than the number of (biological) samples. Modern advances in statistical data analyses allow for the appropriate analysis of such data. Methods for the analysis of high dimensional data rely heavily on multivariate statistical methods. Therefore a large part of the course content is devoted to multivariate methods, but with a focus on high dimensional settings and issues. Multivariate statistical analysis covers many methods. In this course a selection of techniques is covered based on our experience that they are frequently used in industry and research institutes. The course is taught using case studies with applications from different fields (analytical chemistry, ecology, biotechnology, genomics, …).
This course targets professionals and investigators from all areas that are high-dimensional.
Course prerequisites are ready at hand knowledge of basic statistics: data exploration and descriptive statistics, statistical modeling, and inference: linear models, confidence intervals, t-tests, F-tests, anova, chi-squared test, such as covered in Module 4 - Drawing Conclusions from Data: an Introduction, Module 8 - Exploiting Sources of Variation in your Data: the ANOVA Approach and Module 11 - Explaining and Predicting Outcomes with Linear Regression of this years' course program.
There is no exam connected to this module. If you attend all classes you will receive a certificate of attendance via e-mail at the end of the course.
The 6st, 8th, 13th, 15th, 20th & 22nd of February 2024 from 5.30 pm to 9,30 pm.
Faculty of Science, Campus Sterre, Krijgslaan 281, 9000 Ghent, Building S1 Room 3.2 & S9 Auditorium 3.
The participation fee is 1320 EUR for participants from the private sector. Reduced prices apply to students and staff from non-profit, social profit, and government organizations.
*If two or more employees from the same company enrol simultaneously for this course a reduction of 20% on the course fee is taken into account starting from the second enrolment.
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As UGent PhD student you can incorporate this 'specialist course' in your Doctoral Training Program (DTP). To get a refund of the registration fee from your Doctoral School (DS) please follow these strict rules and take the necessary action in time. The deadline to open a dossier on the DS website (Application for Registration) for this course is January 4, 2024.
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Information on "KMO-portefeuille": https://www.ugent.be/nl/opleidingen/levenslang-leren/kmo
Academy for Lifelong Learning (IPVW)
Faculty of Science