Women of Mathematics: Angelika Wiegele

Country: Austria

Affiliation: Universität Klagenfurt, Austria

Field of Research: combinatorial optimization, semidefinite programming, nonlinear optimization

 

 

1.) Why did you choose this formula?

What you see is a semidefinite program, which can be used to approximate many hard discrete problems. However, solving it is still challenging and that’s what I am working on.

 

2.) What made you decide to study Mathematics?

It was just the way things turned out.

 

3.) What do you like so much about Mathematics?

The clear and concise language. Also, I like the fact that you work on something and you think about it over and over again, try things out in several ways, and suddenly you get the idea or understand it; and then everything seems to become clear, and it’s done.

 

4.) How does Mathematics influence our lives on a daily basis?

Mathematics influences our life to the extent that many things in our modern world would not exist without it. For example, without mathematics, our mobile phones wouldn’t work.

 

5.) Have you experienced a special Mathematics moment?

Not that I‘m aware of 😉

 

6.) What advice would you give future mathematicians to help them on their way?

Be patient and increase your tolerance for frustration.

 

 

Vortrag: Auf dem Weg der angewandten Statistik in die Data-Science-Zukunft, Herausforderungen und Chancen für die Alpen-Adria Universität

Vortrag, gehalten an der Zehnjahresfeier des Instituts für Statistik am 1. Dez. 2017.

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The Stork Brings the Babies: Understanding Statistics Properly

In an increasing way, analysing data reigns the world: Amazon calculates what we want to shop, Google interprets by our Internet search behaviour who we are, health care is based on statistics. Manfred Borovcnik identifies a demand for the extension of competences with respect to understanding statistics properly.

 

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Kinder kommen von Störchen: Statistik richtig verstehen

Auswertungen von Datenbeständen regieren zunehmend die Welt: Amazon errechnet, was wir kaufen wollen, Google interpretiert anhand von Suchanfragen, wer wir sind, die Gesundheitsvorsorge fußt auf Statistik. Manfred Borovcnik ortet Kompetenzerweiterungsbedarf für das Verstehen von Statistik.

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Mathematik-Olympiade-Kurse für SchülerInnen an der AAU

Sie kennen Schülerinnen und Schüler, die den normalen Mathematik-Unterricht in der Schule leicht finden oder großen Spaß am Rätseln haben? Dann sind die Mathematik-Olympiade-Kurse am Institut für Mathematik genau das Richtige! Weiterlesen

10 Years Department of Statistics

10 Jahre Institut für Statistik an der Alpen-Adria-Universität Klagenfurt

Wann: Freitag, 1. Dezember 2017, 14 s.t. – 18 Uhr

Wo: Hörsaal 10, Mensagebäude, Universitätsstraße 90, Klagenfurt

Feier zum zehnjährigen Bestand des Instituts für Statistik an der Fakultät für Technische Wissenschaften

Programm http://wwwg.uni-klu.ac.at/stochastik.schule/Boro/Veranstaltungen/Stat_10J_Einladung.pdf

Wir freuen uns auf Ihr Kommen! Wenn Sie etwas zu unserer Feier beitragen möchten, nehmen Sie bitte mit uns Kontakt auf.
Manfred Borovcnik und Jürgen Pilz
Vorstand und Stellvertretender Vorstand des Instituts für Statistik

Um Anmeldung wird bis zum 27. November gebeten, jedenfalls wenn Sie am kleinen Buffet, das wir gerne bereitstellen wollen, „mitnaschen“ möchten.

Kontakt: DDipl.-Ing. Johannes Winkler johannes [dot] winkler [at] aau [dot] at

A Comparative Study of Statistical Inference from an Educational Point of View

Invited Paper Session 116, 61st World Statistics Congress; Marrakech, 16.-21.7.2017
Organiser: Manfred Borovcnik, Universität Klagenfurt
Chair: Michael G. Schimek, MedUniversität Graz
Discussant: Jan Hannig, University of North Carolina at Chapel Hill
Speakers:

  • Robert delMas, University of Minnesota, USA: A 21st Century Approach towards Statistical Inference – Re-Randomization, Resampling, and Bootstrap to Replace Traditional Statistical Inference
  • Min-ge Xie, Rutgers University, New Jersey, USA: Urging A Paradigm Change: An Introduction to BFF (Bayesian, Frequentist And Fiducial) Inferences and how Bayesian and Frequentist Come together
  • Dalene Stangl, Duke University, Durham, USA: Informal Inference – Some Thoughts to Reconsider
  • Manfred Borovcnik, University of Klagenfurt, Austria: Why and how to Train Introductory Statistics Students in Bayesian Thinking – A Decision-Oriented Approach towards Statistical Inference

The aim of the session is to initiate a critical discussion about

  • classical methods of statistical inference
  • the Bayesian approach to inference,
  • a decision-oriented approach to inference,
  • using resampling in inference

The latter resampling school has gained massive attention within the statistics education community (starting with Cobb, 2007). The principal aim is to discuss merits and disadvantages of the various approaches towards statistical inference. A side goal is to find a legitimation for statistical inference in the curriculum of secondary schools and debate on possibilities of teaching statistical inference in the era of big data.
The resampling approach is intended to replace all other approaches towards inference in statistical education from high school to undergraduate studies. The argument is said to be evidence-based with studies to show that students acquire better competencies. The solutions are easily implemented by simulation, or better, by resampling the data. However, probability is completely reduced to frequencies and all information is perfectly contained in data – any extra hypotheses or prior knowledge are excluded from consideration. Such a session to discuss the relative merits of the various approaches towards statistical inference is urgently needed. At ICOTS 9 in Flagstaff there have been two complete sessions focusing entirely on the informal approach (of re-randomization and resampling including bootstrap). Though this way may be good as a transient stage towards statistical inference, its strengths and limitations should also be investigated, especially what it can achieve and whether it can stand for itself.
One speaker in the session will take the position of „informal inference”, one will take a Bayesian view, a third representing a decision-oriented approach, and a fourth to balance the benefits and drawbacks after presenting the classical view.
This would continue the endeavour of the late-breaking session “Statistical Inference – an Unresolved Issue in Statistics Education” at the WSC in Hong Kong to develop a comparative study of teaching statistical inference. The considerations will be qualitative scientific argument as well as empirical evidence. As Barnett (1973) analysed statistical inference from a comparative perspective to shed light on the various approaches, which all have their benefits and drawbacks, we should analyse the grand scenario of statistics education from a comparative perspective and investigate the relative merits and limitations of reducing the concept of probability to a pure frequentist concept. The various schools of statistical inference may no longer be needed.

Verleihung einer Ehrenprofessur an Prof. DDr. Michael G. Schimek

Festakt, Donau-Universität Krems, 16. 2. 2017, 17.00
Zur Würdigung außerordentlicher Verdienste in Forschung und Lehre.

Neuerscheinung zur Didaktik der Statistik und Wahrscheinlichkeit

Carmen Batanero (Universidad de Granada) und Manfred Borovcnik (Alpen-Adria-Universität) haben aktuell ein Handbuch mit dem Titel „Statistics and Probability in High School“ herausgegeben. Das Buch wendet sich an Lehrkräfte der Sekundarstufe II und an all jene Personen, die in der Aus- und Weiterbildung von Lehrkräften tätig sind.

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