Vorlesungsverzeichnis

Suchen Sie hier über ein Suchformular im Vorlesungsverzeichnis der Leuphana.

Veranstaltungen von Dr. Jan-Bennet Voltmer


Lehrveranstaltungen

Quantitative Data Analysis in R: The Tidyverse Approach (Seminar)

Dozent/in: Jan-Bennet Voltmer, Katharina Voltmer

Termin:
Einzeltermin | Fr, 28.10.2022, 14:15 - Fr, 28.10.2022, 19:45 | Online-Veranstaltung | Online
Einzeltermin | Fr, 04.11.2022, 14:15 - Fr, 04.11.2022, 19:45 | C 11.320 | .
Einzeltermin | Sa, 05.11.2022, 10:15 - Sa, 05.11.2022, 19:45 | C 11.307 | .

Inhalt: Why not Python? "People have divided the Data Science field into camps based on the choice of the programming language they use. There is an R camp and a Python camp and history is a testimony to the fact that camps cannot live in harmony. Members of both the camps fervently believe that their choice of language is superior to the other. So, in a way, divergence doesn’t lie with the tools but with the people using those tools." (Pandey, 2019) "R is developed by academics and scientist. It is designed to answer statistical problems, machine learning, and data science. R is the right tool for data science because of its powerful communication libraries. [...] After you know your first programming language, learning the second one is simpler." Therefore, participants will practice the programming language R using prepared syntax. Participants will work on small programming tasks on their own and in small groups to practice and deepen their statistics and R skills. In particular, the seminar will focus on the relatively new but very intuitive “tidyverse” approach of R programming. This consists of some very easily relatable “verbs” (i.e., select, filter, mutate, group_by, summarize), to ease accessibility of R analyses.

Zombies, Robots, Sex, Drugs, and Rock'n'Roll. Z-Standardization, Residuals, Statistics, and Data Analysis in R. (Seminar)

Dozent/in: Jan-Bennet Voltmer

Termin:
Einzeltermin | Fr, 04.11.2022, 14:15 - Fr, 04.11.2022, 19:45 | C 14.201 | .
Einzeltermin | Sa, 19.11.2022, 10:15 - Sa, 19.11.2022, 17:45 | C 14.201 | .
Einzeltermin | Sa, 26.11.2022, 10:15 - Sa, 26.11.2022, 17:45 | C 14.103 | .
Einzeltermin | Fr, 13.01.2023, 14:15 - Fr, 13.01.2023, 15:45 | C 12.111 | .

Inhalt: *** The statistics and novel part of the seminar *** "Where would the hipsters of psychology, medicine, business studies and biology be without statistics? They’d be setting fire to their own pants at a party: happier, perhaps, but directionless and in danger of getting burned. So don’t run away or fear statistics. Strike up a conversation with it, be patient and kind and see what happens.” (Field, 2016) Working with data, both qualitative and quantitative, is one of the core competencies for scientists (and scientists-to-be). In the seminar, students will gain a deep understanding of basic descriptive and inferential statistics, covering topics from measures of central tendency (mode, median, and mean) to multiple linear regression with interaction effects. Students will practice the use of their statistical knowledge in one of the most wide-spread statistic softwares, the open source software "R". For that means, students will work through the ground-breaking statistics book "An Adventure in Statistics. The Reality Enigma" (Field, 2016), containing (1) a sci-fi lovestory, (2) graphic novel elements, and (3) a comprehensive statistics textbook. “At a simple level ‘an adventure in statistics’ is a story about Zach searching for Alice, and seeking the truth, but it’s also about the unlikely friendship he develops with a sarcastic cat, it’s about him facing his fear of science and numbers, it’s about him learning to believe in himself. It’s a story about love, about not forgetting who you are. It’s about searching for the heartbeats that hide in the gaps between you and the people you love. It’s about having faith in others. Of course, it’s also about fitting models, robust methods, classical and Bayesian estimation, significance testing and whole bunch of other tedious statistical things, but hopefully you’ll be so engrossed in the story that you won’t notice them. Or they might be a welcome relief from the terrible fiction. Time will tell.“ (Field, 2016) In small groups, students will prepare and conduct presentations on the book chapters. The presentations will cover both, the fictional story as well as the statistical knowledge. *** The data analysis part of the seminar (aka: why you no teaching Python?) *** "People have divided the Data Science field into camps based on the choice of the programming language they use. There is an R camp and a Python camp and history is a testimony to the fact that camps cannot live in harmony. Members of both the camps fervently believe that their choice of language is superior to the other. So, in a way, divergence doesn’t lie with the tools but with the people using those tools." (Pandey, 2019) "R is developed by academics and scientist. It is designed to answer statistical problems, machine learning, and data science. R is the right tool for data science because of its powerful communication libraries. [...] After you know your first programming language, learning the second one is simpler." Therefore, students will practice the programming language R using prepared syntax. Students work on small programming tasks on their own and in small groups to practice and deepen their statistics and R skills.