Symbol Kurs

Basic Stats with R

Basic concepts of stochastic: distributions, expected value, variance, covariance; Basic concepts of statistics: samples, mean value, quantiles, correlation; Intuitive statistics: Scatter diagrams, box plots; Estimators: Estimators for expected value and variance, hypothesis testing, linear regression; Learning objectives: The students understand the basic concepts of stochastic and statistics; can perform calculations with the concepts of stochastic and statistics; can observe statistical properties of samples from plots of the data; are able to estimate the properties of a distribution from a sample; Prerequisites: Basic arithmetics and algebra, basic calculus For Students from Ukraine: Welcome! We are happy about your participation in this course. Please note that the assessment of the course may have to be arranged separately to the other students. You will be informed about this in good time in the forum / by e-mail.

Allgemeine Informationen

Wichtige Informationen

Basic concepts of stochastic: distributions, expected value, variance, covariance; Basic concepts of statistics: samples, mean value, quantiles, correlation; Intuitive statistics: Scatter diagrams, box plots; Estimators: Estimators for expected value and variance, hypothesis testing, linear regression; Learning objectives: The students understand the basic concepts of stochastic and statistics; can perform calculations with the concepts of stochastic and statistics; can observe statistical properties of samples from plots of the data; are able to estimate the properties of a distribution from a sample; Prerequisites: Basic arithmetics and algebra, basic calculus

For Students from Ukraine: Welcome! We are happy about  your participation in this course. Please note that the assessment of the course may have to be arranged separately to the other students. You will be informed about this in good time in the forum (only if available in the course!) / by e-mail.

Kursprogramm

The course covers the following topics:

1. Introduction
2. Data sets
3. Analizing data sets  (concpets and use of R)
4. Linear regression models
5. Probability and  distributions
6. Estimates and tests
7. Mulitvariate data sets

Tutorielle Betreuung

Dr. Wigand Rathmann

Adresse

Cauerstraße 11, Raum 03.317 (3. OG)
91058 Erlangen

Institution

FAU

Kontakt

Telefon Arbeit: 09131 85-67129
E-Mail: wigand.rathmann@fau.de

Homepage

datascience.nat.fau.eu/research/researchers/wigand-rathmann/

Verfügbarkeit

Zugriff
Unbegrenzt – wenn online geschaltet
Aufnahmeverfahren
Sie müssen einen Aufnahmeantrag stellen. Im Feld Nachricht, haben Sie die Möglichkeit zu beschreiben, warum Sie beitreten möchten. Diese Nachricht ist optional. Sobald Ihr Antrag angenommen oder abgelehnt wurde, erhalten Sie eine Benachrichtigung.
Zeitraum für Beitritte
12. Sep 2022, 10:30 - 11. Feb 2023, 17:30
Chancengleich bis
13. Sep 2022, 12:00
Freie Plätze
6

Für Kursadministratoren freigegebene Daten

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