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

flag 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.
International Tourism-Management, Bachelor, ASPO 01.10.2020
Module code: BITM-231
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.
P420-0452
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.
4V+2U (6 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:
English
Assessment:
Written exam (90 minutes / Can be repeated semesterly)

[updated 14.11.2022]
Applicability / Curricular relevance:
All study programs (with year of the version of study regulations) containing the course.

BITM-231 (P420-0452) International Tourism-Management, Bachelor, ASPO 01.10.2020 , semester 2, mandatory course

Suitable for exchange students (learning agreement)
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).
90 class hours (= 67.5 clock hours) over a 15-week period.
The total student study time is 150 hours (equivalent to 5 ECTS credits).
There are therefore 82.5 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
BITM-141 Mathematics


[updated 06.03.2020]
Recommended as prerequisite for:
Module coordinator:
Prof. Dr. Teresa Melo
Lecturer: Prof. Dr. Teresa Melo

[updated 25.11.2019]
Learning outcomes:
After successfully completing this module, students will be able to:
  
- explain basic concepts of descriptive statistics for univariate and bivariate data analysis
- select appropriate methods for statistical data analysis and apply them in the context of business applications
- create visual representations of data
- analyze, quantify and interpret relationships between two variables
- describe and model random phenomena using concepts from the probability theory
- explain basic probability rules and apply them to exemplary business statistical problems  
- calculate and interpret probabilities  
- apply special discrete and continuous probability distributions to business applications (e. g. binomial and normal distributions)
- interpret and communicate the results obtained from a statistical analysis.


[updated 14.11.2022]
Module content:
Descriptive statistics:
 
- Data sources and data collection methods
- Types of variables and scales of measurement
- Tabulation of frequency distributions for grouped and non-grouped data
- Displaying categorical and quantitative data
- Description of univariate data sets using measures of location and dispersion
- Bivariate data analysis: graphical representation of data sets, cross tabulation, measures of association and correlation (contingency, correlation, rank correlation)
- Simple linear regression
 
 
Probability theory:
 
- Definition of probability and basic concepts
- Fundamentals of set theory
- Empirical interpretation of probabilities (Laplace probability, statistical probability, subjective probability)
- Axioms of Kolmogorov
- Elementary calculation rules
- Conditional probabilities
- Stochastic independent events
- Total probability, Bayes´ rule
- Discrete and continuous random variables
- Special probability models (e.g. Bernoulli, binomial and normal distributions)


[updated 14.11.2022]
Teaching methods/Media:
Lectures supported by slides (projector) and blackboard (theory and example calculations). The lectures are supplemented by exercises and tutorials. In order to support independent work, multiple exercise sheets covering the whole range of topics in this module are provided. Solutions are discussed with the students in the tutorials. Both the lecture notes and the exercise sheets are available to students in electronic form.

[updated 14.11.2022]
Recommended or required reading:
Bowerman, O’Connell, Murphree: Business Statistics in Practice, international edition, 6th edition, McGraw-Hill/Irvin, 2011
OpenStax College: Introductory Business Statistics, OpenStax CNX, https://openstax.org/details/books/introductory-business-statistics, 2019
Sharpe, De Veaux, Velleman: Business Statistics, 3rd edition, Pearson, 2015
Sweeney, Williams, Anderson: Fundamentals of Business Statistics, international edition, 6th edition, Cengage Learning Emea, 2011
Weiers: Introductory Business Statistics, international edition, 7th edition, Cengage Learning Emea, 2011


[updated 14.11.2022]
 
[Tue Dec 24 04:07:50 CET 2024, CKEY=isg, BKEY=itm5, CID=BITM-231, LANGUAGE=en, DATE=24.12.2024]