htw saar QR-encoded URL
Back to Main Page Choose Module Version:
XML-Code

flag


Statistics

Module name (EN):
Name of module in study programme. It should be precise and clear.
Statistics
Degree programme:
Study Programme with validity of corresponding study regulations containing this module.
Industrial Engineering, Bachelor, ASPO 01.10.2013
Module code: WIBASc255
SAP-Submodule-No.:
The exam administration creates a SAP-Submodule-No for every exam type in every module. The SAP-Submodule-No is equal for the same module in different study programs.
P450-0088
Hours per semester week / Teaching method:
The count of hours per week is a combination of lecture (V for German Vorlesung), exercise (U for Übung), practice (P) oder project (PA). For example a course of the form 2V+2U has 2 hours of lecture and 2 hours of exercise per week.
2V+2U (4 hours per week)
ECTS credits:
European Credit Transfer System. Points for successful completion of a course. Each ECTS point represents a workload of 30 hours.
5
Semester: 2
Mandatory course: yes
Language of instruction:
German
Assessment:
Written or oral examination. The type of examination will be announced on the notice board at the beginning of the course.

[updated 02.07.2019]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

WIBASc255 (P450-0088) Industrial Engineering, Bachelor, ASPO 01.10.2013 , semester 2, mandatory course
Workload:
Workload of student for successfully completing the course. Each ECTS credit represents 30 working hours. These are the combined effort of face-to-face time, post-processing the subject of the lecture, exercises and preparation for the exam.

The total workload is distributed on the semester (01.04.-30.09. during the summer term, 01.10.-31.03. during the winter term).
60 class hours (= 45 clock hours) over a 15-week period.
The total student study time is 150 hours (equivalent to 5 ECTS credits).
There are therefore 105 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
WIBASc165 Mathematics I


[updated 10.02.2020]
Recommended as prerequisite for:
WIBASc-515 Automation Engineering
WIBASc-525-625-FÜ12 Using Mathematical Software
WIBASc-525-625-FÜ15 Market Research
WIBASc-525-625-FÜ19 Simulation II
WIBASc-525-625-FÜ22 Decision theory
WIBASc-525-625-FÜ23 Simulation
WIBASc-525-625-FÜ29 Introduction to Six Sigma


[updated 11.02.2020]
Module coordinator:
Prof. Dr. Susan Pulham
Lecturer:
Prof. Dr. Susan Pulham


[updated 10.02.2020]
Learning outcomes:
After successfully completing this module students will:
_        be able to process mass data with methods of descriptive statistics
_        know how to interpret the results of the above
_        be able to recognize stochastic situations as such and can model them by stochastic means
_        have acquired the ability to calculate probabilities, determine suitable distribution forms and calculate distribution parameters
_        have a basic understanding of inductive statistics, especially methods of estimating parameters and testing hypotheses


[updated 02.07.2019]
Module content:
1. Descriptive statistics:
_        Basic terms
_        One- and two-dimensional frequency distributions
_        Measures of location and measures of spread/dispersion
_        Calculating correlation and regression
 
2. Probability calculus
_        Basic terms: random experiment, events, probability
_        Modeling
_        Multi-stage random experiments
_        Conditional probability and independence
_        Random variables, expected value, variance, normal distribution and limit theorems
 
3. Basic elements of the inferential statistics
_        Problems of inferential statistics
_        Point and interval estimates
_        Hypothesis tests


[updated 02.07.2019]
Teaching methods/Media:
Excel files with sample material, press reports and statistical studies will be used. Regularly revised lecture notes will be available for this course.

[updated 02.07.2019]
Recommended or required reading:
_        Dietmaier, C.: Mathematik für Wirtschaftsingenieure, 1. Auflage, Carl Hanser Verlag, 2005
_        Eckstein, Peter: Statistik für Wirtschaftswissenschaftler, 3. Auflage, Gabler, Wiesbaden, 2011
_        Fischer, Gerd: Stochastik einmal anders; 1. Auflage, Vieweg+Teubner Verlag, Wiesbaden, 2005.
_        Henze, Norbert: Stochastik für Einsteiger; 9. Auflage, Vieweg Verlag, Wiesbaden, 2011.
_        Pulham, Susan: Statistik für Nicht-Mathematiker, Gabler, Wiesbaden, 2011
_        Sachs, Michael: Wahrscheinlichkeitsrechnung und Statistik für Ingenieurstudenten an Fachhochschulen; 3. Auflage, Carl Hanser Verlag, 2009


[updated 02.07.2019]
 
[Fri Dec 27 18:04:00 CET 2024, CKEY=wwxs, BKEY=wi2, CID=WIBASc255, LANGUAGE=en, DATE=27.12.2024]