Analyzing and visualizing insurance data

Dozent/in	Lukas Kauer, PhD
Veranstaltungsart	Workshop
Code	FS211210
Semester	Frühjahrssemester 2021
Durchführender Fachbereich	Wirtschaftswissenschaften
Studienstufe	Master
Termin/e	wöchentlich (Mo), ab 22.02.2021, 14:15 - 16:00 Uhr
Umfang	2 Semesterwochenstunden
Turnus	weekly
Inhalt	In most courses on data analysis the students receive fairly clean data with plausible values. Working with data in industry often turns out to be a different story. In this workshop, students will receive a large data set from an insurer which first needs to be checked for inconsistencies and implausibility. Some exercises need to be performed before the students choose a research question which they want to answer with the data set in a term paper. Students will learn how to effectively visualize and present data. They will also improve their data reasoning and ability to discover false claims in data reporting in media and academia.
Lernziele	Handling, management, and visualization of large data sets; improvement of data reasoning and of ability to call out wrong claims from data analysis; phrasing a research question and application of statistical methods to answer it; skills learnt in this class enables the student to write an empirical master thesis.
Voraussetzungen	The student should bring experience in handling and analyzing data; - the following classes are mandatory: Statistik; Angewandte Statistik und Ökonometrie or a similar class - the following classes are recommended: Data handling; Data Analytics and Decision Support; Causal Analysis - good knowledge of a statistical software, with a preference to R
Sprache	Englisch
Begrenzung	Not more than 12 participants
Anmeldung	To attend the course / exercise, registration via e-learning platform OLAT is required. Registration is possible from 8 February to 5 March 2021. The students themselves are responsible for checking the creditability of the course to their course of study. Direct link to OLAT course: https://lms.uzh.ch/url/repositoryentry/16940630174
Prüfung	***IMPORTANT*** In order to acquire credits, registration via the Uni Portal within 08.02. - 05.03.2021 is REQUIRED.
Abschlussform / Credits	Individual/group presentation; written assignment / 3 Credits
Hörer-/innen	Nach Vereinbarung
Kontakt	lukas.kauer@doz.unilu.ch
Anzahl Anmeldungen	6 von maximal 12
Literatur	Wickham, Hadley und Garett Gorlemund (2017). R for Data Science. O’Reilly. https://r4ds.had.co.nz/ Healy, Kieran (2019) Data Visualization – A Practical Introduction. Princeton. https://socviz.co/ Wilke, Claus (2019) Fundamentals of Data Visualization, https://clauswilke.com/dataviz/