311.990 (24S) Methodology 2: Statistics

Sommersemester 2024

Anmeldefrist abgelaufen.

Erster Termin der LV
07.03.2024 12:15 - 13:45 HS 10 On Campus
Nächster Termin:
02.05.2024 12:15 - 13:45 HS 10 On Campus

Überblick

Lehrende/r
LV-Titel englisch Methodology 2: Statistics
LV-Art Vorlesung
LV-Modell Präsenzlehrveranstaltung
Semesterstunde/n 2.0
ECTS-Anrechnungspunkte 4.0
Anmeldungen 145
Organisationseinheit
Unterrichtssprache Englisch
LV-Beginn 07.03.2024
eLearning zum Moodle-Kurs
Anmerkungen

- For organisational matters, please contact office.stat@aau.at
- For content-related questions, please use the respective forum on Moodle, or simply ask the question in the lectures/tutorials

Seniorstudium Liberale Ja

Zeit und Ort

Liste der Termine wird geladen...

LV-Beschreibung

Intendierte Lernergebnisse

More and more data is becoming available in all areas of Business and Economics; one of its use-cases is to build and back hypotheses such as purchase decisions by customers. Transforming data into scientific theories requires tools which are known as statistical methods.

"Methodology 2: Statistics" aims at providing a fundamental knowledge about these tools by analyzing univariate and multivariate data sets. Examples are
- descriptive statistics
- estimation, prediction, and testing of proportions and means
- analysis of variance
- contingency tables
- linear regression

The lecture is accompanied by a KS with the same name, in which exercises and case studies will be solved by the students using the statistical software R.

Lehrmethodik

Lectures with active and passive parts, accompanied by eLearning-material. Individual practice through exercises, case studies, and quizzes.

Inhalt/e

- data, variables, frequencies
- descriptive statistics
- estimating, predicting, and testing of proportions
- estimating, predicting, and testing of means
- comparison of means
- analysis of variance (ANOVA)
- contingency tables and chi-square-test
- linear regression

Erwartete Vorkenntnisse

basic mathematical and statistical knowledge at high-school level, in particular:
- basic arithmetic
- elementary probability calculus and probability distributions (binomial and normal distribution)
- successful completion of "Methodology 1: Mathematics" highly recommended

Curriculare Anmeldevoraussetzungen

Please combine with "KS Methodology 2: Statistics"

Intendierte Lernergebnisse

More and more data is becoming available in all areas of Business and Economics; one of its use-cases is to build and back hypotheses such as purchase decisions by customers. Transforming data into scientific theories requires tools which are known as statistical methods.

"Methodology 2: Statistics" aims at providing a fundamental knowledge about these tools by analyzing univariate and multivariate data sets. Examples are descriptive statistics, estimation, prediction, and testing of proportions and means, analysis of variance, contingency tables, linear regression, and model selection.

The lecture is accompanied by a KS with the same name, in which exercises and case studies will be solved by the students using the statistical software R.

Lehrmethodik

Lectures with active and passive parts, accompanied by eLearning material. Individual practice through exercises, case studies, and quizzes.

Inhalt/e

  • data, variables, frequencies
  • descriptive statistics
  • estimating, predicting, and testing of proportions
  • estimating, predicting, and testing of means
  • comparison of means
  • analysis of variance (ANOVA)
  • contingency tables and chi-square-test
  • linear regression

Erwartete Vorkenntnisse

basic mathematical and statistical knowledge at high-school level, in particular:

  • basic arithmetic
  • elementary probability calculus and probability distributions (binomial and normal distribution)
  • successful completion of "Methodology 1: Mathematics" highly recommended

Curriculare Anmeldevoraussetzungen

Please combine with "KS Methodology 2: Statistics"

Prüfungsinformationen

Im Fall von online durchgeführten Prüfungen sind die Standards zu beachten, die die technischen Geräte der Studierenden erfüllen müssen, um an diesen Prüfungen teilnehmen zu können.

Prüfungsmethode/n

Written (digital) exam in English. Exam dates: last week of June and three further dates throughout the following term (late September / early October, November, and January). The exact dates will be announced once the dates and locations are fixed.

first exam: last week of June

second exam: first week of October

third exam: mid November

fourth exam: last week of January

Prüfungsinhalt/e

Content of lectures, quizzes, and supplementary online material.

Beurteilungskriterien/-maßstäbe

Written (online) exam.

Prüfungsmethode/n

Written (digital) exam in English. Exam dates: last week of June and three further dates throughout the following term (late September / early October, November, and January). The exact dates will be announced once the dates and locations are fixed.

first exam: TBA

second exam: TBA

third exam: TBA

fourth exam: TBA

Prüfungsinhalt/e

Content of the lectures.

Beurteilungskriterien/-maßstäbe

Written (online) exam.

Beurteilungsschema

Note Benotungsschema

Position im Curriculum

  • Bachelorstudium Betriebswirtschaft (SKZ: 518, Version: 18W.1)
    • Fach: Methoden der Sozial- und Wirtschaftswissenschaften (Pflichtfach)
      • 5.2 Methoden II: Statistik ( 0.0h VO/ VI / 4.0 ECTS)
        • 311.990 Methodology 2: Statistics (2.0h VO / 4.0 ECTS)
          Absolvierung im 1., 2., 3. Semester empfohlen
  • Bachelorstudium Angewandte Betriebswirtschaft (SKZ: 518, Version: 14W.3)
    • Fach: Mathematik und Statistik für Wirschaftswissenschaften (Pflichtfach)
      • §9(1) Statistik für Wirtschaftswissenschaften ( 2.0h VO / 4.0 ECTS)
        • 311.990 Methodology 2: Statistics (2.0h VO / 4.0 ECTS)
  • Bachelorstudium Informationsmanagement (SKZ: 522, Version: 17W.1)
    • Fach: Wahlfach Mathematik und Statistik (ABWL) (Wahlfach)
      • 5.1.2 Statistik für Wirtschaftswissenschaften ( 0.0h VO / 4.0 ECTS)
        • 311.990 Methodology 2: Statistics (2.0h VO / 4.0 ECTS)
          Absolvierung im 2. Semester empfohlen
  • Bachelorstudium Wirtschaftsinformatik (SKZ: 522, Version: 20W.2)
    • Fach: Mathematik und Statistik (Betriebswirtschaft) (Wahlfach)
      • 7.1.2 Statistik ( 0.0h VO, VI / 4.0 ECTS)
        • 311.990 Methodology 2: Statistics (2.0h VO / 4.0 ECTS)
          Absolvierung im 2. Semester empfohlen
  • Bachelorstudium International Business and Economics (SKZ: 516, Version: 19W.1)
    • Fach: Methodology in Business and Economics Research (Pflichtfach)
      • 7.2 Methodology 2 ( 0.0h VO, VI / 4.0 ECTS)
        • 311.990 Methodology 2: Statistics (2.0h VO / 4.0 ECTS)
          Absolvierung im 1., 2., 3. Semester empfohlen

Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung

Wintersemester 2023/24
  • 311.970 VO Methoden II: Statistik (2.0h / 4.0ECTS)
Sommersemester 2023
  • 311.990 VO Methodology 2: Statistics (2.0h / 4.0ECTS)
Wintersemester 2022/23
  • 311.970 VO Methoden II: Statistik (2.0h / 4.0ECTS)
Sommersemester 2022
  • 311.990 VO Methodology 2: Statistics (2.0h / 4.0ECTS)
Wintersemester 2021/22
  • 311.970 VO Methoden II: Statistik (2.0h / 4.0ECTS)
Sommersemester 2021
  • 311.970 VO Methoden II: Statistik (2.0h / 4.0ECTS)
Wintersemester 2020/21
  • 311.990 VO Methodology 2: Statistics (2.0h / 4.0ECTS)
Sommersemester 2020
  • 311.970 VO Methoden II: Statistik (2.0h / 4.0ECTS)
Wintersemester 2019/20
  • 311.990 VO Methodology 2: Statistics (2.0h / 4.0ECTS)
Sommersemester 2019
  • 311.970 VO Statistik für Wirtschaftswissenschaften (2.0h / 4.0ECTS)
Sommersemester 2018
  • 311.970 VO Statistik für Wirtschaftswissenschaften (2.0h / 4.0ECTS)
Sommersemester 2017
  • 311.970 VO Statistik für Wirtschaftswissenschaften (2.0h / 4.0ECTS)
Sommersemester 2016
  • 311.970 VO Statistik für Wirtschaftswissenschaften (2.0h / 4.0ECTS)
Sommersemester 2015
  • 311.970 VO Statistik für Wirtschaftswissenschaften (2.0h / 4.0ECTS)
Sommersemester 2014
  • 310.870 VO Statistik für Wirtschaftswissenschaften (2.0h / 4.0ECTS)
Sommersemester 2013
  • 310.870 VO Statistik für Wirtschaftswissenschaften (2.0h / 4.0ECTS)