311.170 (18W) Stochastics 1

Wintersemester 2018/19

Registration deadline has expired.

First course session
04.10.2018 09:00 - 10:00 HS 10 On Campus
... no further dates known

Overview

Lecturer
LV Nummer Südostverbund MAF01001UL
Course title german Stochastik 1
Type Lecture - Practical class (continuous assessment course )
Hours per Week 3.0
ECTS credits 4.5
Registrations 118 (20 max.)
Organisational unit
Language of instruction German
Course begins on 04.10.2018
eLearning Go to Moodle course
Remarks (english)

The type of the course is VU, which means exercises and lecture are integrated. In fact, we will have a lecture on Fridays (2 hours) and the exercises on Thursdays (presence will be controlled). The exercises part (1 hour) will be split into groups. This is different from what is shown in ZEUS.

Time and place

List of events is loading...

Course Information

Intended learning outcomes

  • To develop competencies to recognize and model real situations by probabilistic notions.
  • Recognize random situations in reality and being able to model them adequately. 
  • To be able to appreciate or critise stochastic models used in public debate or in scientific argument.
  • To acquire practical competencies to apply the concepts of the lecture part to practical problems. 
  • To illustrate the theoretical notions of the accompanying course.

Topics

1. Elementary probability
    1.a Random situations and probabilities
    1.b Combinatorics
    1.c Conditional probabilities and Bayes formula

2. Random variables and distributions
    2.a Types and parameters of distributions (includ. Chebyshev’s inequality)
    2.b Discrete and continuous distributions
    2.c Mathematical extensions: Measure theory, interpretation of concepts, technology

3. Joint distributions and limit theorems
     3.a Joint and marginal distributions
     3.b Weak law of large numbers and central limit theorem
     3.c Mathematical extensions: Multivariate normal, Poisson process, Simulation

4. Random samples and statistical inference
    4.a Random samples
    4.b Statistics from normal samples (chi-square, t, F distributions)  
    4.c Confidence intervals for unknown parameters
    4.d Random numbers and the simulation method

Teaching methodology including the use of eLearning tools

Lecture and exercises

Prior knowledge expected

Knowledge from secondary schools; first course of calculus at university; simple combinatorial counting methods.

Literature

M. Borovcnik (2013): Stochastik 1. Klagenfurt.

Mosler, K. & Schmid, F. (2010): Wahrscheinlichkeitsrechnung und schließende Statistik. Berlin: Springer.

Grinstead, C.M. & Snell, J.L. (2005): Introduction to Probability. Raleigh: American Mathematical Society (AMS). Online: http://www.dartmouth.edu/~chance/teaching_aids/books_articles/probability_book/amsbook.mac.pdf

Examination information

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.

Examination methodology

For the exercise part:

  • Oral exam on set tasks; group discussion; written reading reports

For the course there will be a written exam paper with 2 sections:

  • i. theory (weight/time 1 hour)
  • ii. tasks (weight/time 2 hours)

The exam time for the course of three hours is intended to allow for stress-reduced working.

  • First exam date: 6 February 2019 18.30 – 21.30 HS A 

Examination topic(s)

For the exercise part:

  • Solve the weekly set of 5 tasks mainly by oneself and present the solutions.
  • Deliver the weekly reading task (in small-group collaboration)

For the lecture part:

  1. Tasks (similar to the exercises during the term; extra material and excel or R as software allowed).
  2. Themes (overview questions; no materials, no textbooks, etc. admitted).

Assessment criteria / Standards of assessment for examinations

The final grading is by a written exam to which students are admitted only if they pass the exercises part.

For the exercises part (weekly, 5 tasks are given on the current concepts of the lecture part), the following requirements have to be fulfilled for a pass:

  1.  At least 50% of the weekly set tasks have to be checked in ZEUS.
  2.  Students have to report freely on their solution at the blackboard and participate in general discussion.
  3.  Included in the exercise part grading are the written summary reports on reading tasks (team work).

For the lecture part:

  • Both sections have to be positive, i.e., at least 50% of the maximal points.

Grading scheme

Grade / Grade grading scheme

Position in the curriculum

  • Bachelor-Lehramtsstudium Bachelor Unterrichtsfach Mathematik (SKZ: 420, Version: 15W.2)
    • Subject: Stochastik (Compulsory subject)
      • MAF.001 Stochastik 1 ( 3.0h VU, SE / 4.5 ECTS)
        • 311.170 Stochastics 1 (3.0h VU / 4.5 ECTS)
          Absolvierung im 5. Semester empfohlen
  • Bachelor-Lehramtsstudium Bachelor Unterrichtsfach Mathematik (SKZ: 420, Version: 17W.2)
    • Subject: Stochastik (Compulsory subject)
      • MAF.001 Stochastik 1 ( 3.0h VU, SE / 4.5 ECTS)
        • 311.170 Stochastics 1 (3.0h VU / 4.5 ECTS)
          Absolvierung im 5. Semester empfohlen
  • Teacher training programme Mathematics (Secondary School Teacher Accreditation) (SKZ: 406, Version: 04W.7)
    • Stage two
      • Subject: Stochastik (LM 2.3.) (Compulsory subject)
        • Stochastik I und II ( 4.0h VO / 5.0 ECTS)
          • 311.170 Stochastics 1 (3.0h VU / 4.5 ECTS)
  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 17W.1)
    • Subject: Mathematik und Theoretische Grundlagen (Compulsory subject)
      • 3.5 Stochastik 1 ( 3.0h VU / 4.5 ECTS)
        • 311.170 Stochastics 1 (3.0h VU / 4.5 ECTS)
          Absolvierung im 3. Semester empfohlen
  • Bachelor's degree programme Applied Informatics (SKZ: 511, Version: 12W.1)
    • Subject: Mathematics and Theoretical Principles (Compulsory subject)
      • Stochastics 1 VO+UE ( 3.0h XX / 4.5 ECTS)
        • 311.170 Stochastics 1 (3.0h VU / 4.5 ECTS)
  • Bachelorstudium Informatik (SKZ: 521, Version: 09W.3)
    • Subject: Mathematik und theoretische Grundlagen (Compulsory subject)
      • Stochastics VO+UE ( 3.0h XX / 4.5 ECTS)
        • 311.170 Stochastics 1 (3.0h VU / 4.5 ECTS)
  • Bachelor's degree programme Information Management (SKZ: 522, Version: 17W.1)
    • Subject: Wahlfach Mathematik und Statistik (Informatik) (Compulsory elective)
      • 5.2 Lehrveranstaltungen aus dem Studium Angewandte Informatik/Bereich Mathematik und Statistik für Informatik ( 0.0h VO,KS / 12.0 ECTS)
        • 311.170 Stochastics 1 (3.0h VU / 4.5 ECTS)
  • Bachelor's degree programme Information Management (SKZ: 522, Version: 12W.1)
    • Subject: Wahlfach Mathematik und Statistik (Informatik) (Compulsory elective)
      • 1.1.2 Stochastik ( 0.0h VO / 2.0 ECTS)
        • 311.170 Stochastics 1 (3.0h VU / 4.5 ECTS)
  • Bachelorstudium Informationstechnik (SKZ: 289, Version: 17W.1)
    • Subject: Mathematik II (Compulsory elective)
      • 8a.1 Stochastik 1 ( 0.0h VU / 4.5 ECTS)
        • 311.170 Stochastics 1 (3.0h VU / 4.5 ECTS)
          Absolvierung im 3. Semester empfohlen
  • Bachelorstudium Informationstechnik (SKZ: 289, Version: 17W.1)
    • Subject: Informationstechnische Vertiefung sowie mathematische Ergänzung (Compulsory elective)
      • 10b.2.1 Stochastik 1 ( 0.0h VU / 4.5 ECTS)
        • 311.170 Stochastics 1 (3.0h VU / 4.5 ECTS)
          Absolvierung im 5. Semester empfohlen
  • Bachelor's degree programme Information Technology (SKZ: 289, Version: 12W.2)
    • Subject: Höhere Mathematik II (Compulsory elective)
      • Stochastik 1 VO + KU ( 3.0h XX / 5.0 ECTS)
        • 311.170 Stochastics 1 (3.0h VU / 5.0 ECTS)
          Absolvierung im 3. Semester empfohlen
  • Bachelor's degree programme Information Technology (SKZ: 289, Version: 12W.2)
    • Subject: Informationstechnische Vertiefung sowie mathematische Ergänzung (Compulsory elective)
      • Wahl von Lehrveranstaltungen ( 0.0h VK/VO/KU / 8.0 ECTS)
        • 311.170 Stochastics 1 (3.0h VU / 5.0 ECTS)
  • Bachelorstudium Technische Mathematik (SKZ: 201, Version: 17W.1)
    • Subject: Stochastik (Compulsory subject)
      • 6.1 Stochastik 1 ( 3.0h VU / 4.5 ECTS)
        • 311.170 Stochastics 1 (3.0h VU / 4.5 ECTS)
          Absolvierung im 3. Semester empfohlen
  • Bachelor's degree programme Technical Mathematics (SKZ: 201, Version: 12W.2)
    • Subject: Stochastik (Compulsory subject)
      • Stochastik 1 ( 2.0h VO / 3.0 ECTS)
        • 311.170 Stochastics 1 (3.0h VU / 4.5 ECTS)

Equivalent courses for counting the examination attempts

Wintersemester 2023/24
  • 311.170 VU Stochastik 1 (3.0h / 4.5ECTS)
Wintersemester 2022/23
  • 311.170 VU Stochastik 1 (3.0h / 4.5ECTS)
Wintersemester 2021/22
  • 311.170 VU Stochastik 1 (3.0h / 4.5ECTS)
Wintersemester 2020/21
  • 311.170 VU Stochastik 1 (3.0h / 4.5ECTS)
Wintersemester 2019/20
  • 311.170 VU Stochastik 1 (3.0h / 4.5ECTS)
Wintersemester 2017/18
  • 311.170 VU Stochastik 1 (3.0h / 4.5ECTS)