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60886-01 - Blockkurs: Data Analysis - Descriptive Statistics and Visualisation (2 KP)
| Semester | Frühjahrsemester 2021 |
| Angebotsmuster | unregelmässig |
| Dozierende | Giusi Moffa (giusi.moffa@unibas.ch, BeurteilerIn) |
| Inhalt | This in an introductory course to basic concepts of data description and presentation, and it is designed to provide some essential tools to conduct a statistically sound **exploratory** data analysis and gain familiarity with the widely adopted R statistical software. The course may appeal to both graduate students and applied researchers in quantitative sciences, across any discipline, who wish to explore and describe their own data, as well as to students of mathematics and computer science who are curious about practical applications and wish to have a first experience in simple tasks of real data exploratory analysis. The focus will be on fundamental descriptive statistics for the most common qualitative and quantitative data types, (e.g. binary, continuous, categorical), as well as data visualizations. To illustrate the conceptual ideas we will use real world data examples and will include all the necessary R code to calculate the descriptive statistics and graphical representations we will consider. Additionally we will also cover the essential steps of data management, to enable a complete workflow from a given raw data file to simple tables and plots effectively capturing the main features of the data at hand. |
| Lernziele | The course will run over 4 weeks, with 4 hours a week, where each week two hours will be dedicated to explanatory lectures and two hours will be reserved for the students to put their learning into practice - by applying the notions covered in the lecture to their own data or to other public sample datasets. By the end of the course students should be able to implement a complete exploratory analysis workflow starting from their own raw data file to a few essential tables and plots highlighting important and interesting characteristics of the data under study. |
| Literatur | The course will not follow a specific textbook, but we will provide slides and references as appropriate for each lecture, as well as additional suggested readings and references. |
| Bemerkungen | Due to the very practical nature of the course students should bring a laptop to the lecture, possibly with R (https://www.r-project.org/) and RStudio (https://rstudio.com/) installed. Where needed, we will provide instructions and assistance to install the necessary software during the first practical session, so that all participants will have a functional system for the scope of the course. Further it is expected that the students will need about 2 hours to prepare their laptop with the necessary software before the start of lectures, and will spend about 3 hours a week reviewing the lecture material and working through assignments. |
| Unterrichtssprache | Englisch |
| Einsatz digitaler Medien | kein spezifischer Einsatz |
| HörerInnen willkommen |
| Intervall | Wochentag | Zeit | Raum |
|---|---|---|---|
| wöchentlich | Dienstag | 12.15-14.00 | - Online Präsenz - |
| wöchentlich | Dienstag | 14.15-16.00 | - Online Präsenz - |
| Bemerkungen | Block course from 2.3.21-30.3.21 12-14: Lecture; 14-16: Exercise |
Einzeltermine
| Datum | Zeit | Raum |
|---|---|---|
| Dienstag 02.03.2021 | 12.15-14.00 Uhr | - Online Präsenz -, -- |
| Dienstag 02.03.2021 | 14.15-16.00 Uhr | - Online Präsenz -, -- |
| Dienstag 09.03.2021 | 12.15-14.00 Uhr | - Online Präsenz -, -- |
| Dienstag 09.03.2021 | 14.15-16.00 Uhr | - Online Präsenz -, -- |
| Dienstag 16.03.2021 | 12.15-14.00 Uhr | - Online Präsenz -, -- |
| Dienstag 16.03.2021 | 14.15-16.00 Uhr | - Online Präsenz -, -- |
| Dienstag 23.03.2021 | 12.15-14.00 Uhr | - Online Präsenz -, -- |
| Dienstag 23.03.2021 | 14.15-16.00 Uhr | - Online Präsenz -, -- |
| Dienstag 30.03.2021 | 12.15-14.00 Uhr | - Online Präsenz -, -- |
| Dienstag 30.03.2021 | 14.15-16.00 Uhr | - Online Präsenz -, -- |
| Module |
Modul: Angewandte Mathematik (Bachelorstudium: Mathematik) |
| Prüfung | Lehrveranst.-begleitend |
| An-/Abmeldung zur Prüfung | Anm.: Belegen Lehrveranstaltung; Abm.: stornieren |
| Wiederholungsprüfung | keine Wiederholungsprüfung |
| Skala | 1-6 0,5 |
| Belegen bei Nichtbestehen | beliebig wiederholbar |
| Zuständige Fakultät | Philosophisch-Naturwissenschaftliche Fakultät, studiendekanat-philnat@unibas.ch |
| Anbietende Organisationseinheit | Fachbereich Mathematik |