Information on individual educational components (ECTS-Course descriptions) per semester

Degree programme: Bachelor International Business Part-time
Type of degree: FH Bachelor´s Degree Programme
Part-time
Winter Semester 2021

Course unit title Statistics in Economic Science
Course unit code 025027010202
Language of instruction Deutsch
Type of course unit (compulsory, optional) Compulsory
Semester when the course unit is delivered Winter Semester 2021
Teaching hours per week 3
Year of study 2021
Number of ECTS credits allocated First Cycle (Bachelor)
Number of ECTS credits allocated 5
Name of lecturer(s) Verena BONELL-FOLIE


Prerequisites and co-requisites

None


Course content

Descriptive statistics

  • Scale levels
  • Univariate data analysis (parameters of location and dispersion, frequencies)
  • Evaluation of bivariate and multivariate data sets (contingency coefficient, rank correlation, correlation, regression)

Probability calculation

  • Random variable: probability, density, distribution function
  • Special distributions: hyper-geometric, binomial, normal, t, F, chi-square distribution

Inferential statistics

  • Point estimation - Interval estimation - Hypothesis testing
  • Focus on the analysis of survey data

Learning outcomes

Comprehension

  • Students are able to calculate and interpret those parameters of location and dispersion that are reasonable for given data.
  • Students know the meaning of the term significance.
  • Students understand the basic idea of the confidence interval.
  • Students understand the basic idea of hypothesis testing.

Application 

  • Students are able to clearly display records in tabular and graphical form.
  • Students are able to select the appropriate probabilistic description (distribution) and calculate the probability of typical events of real-world situations.
  • Depending on the available data, students are able to select the appropriate hypothesis tests for a hypotheses of independence and verify the significance of this hypothesis.
  • Students are able to calculate and interpret simple functional relationships using regression analysis and to evaluate the quality of it.
  • Excel can be reasonably applied for statistical evaluations.

Planned learning activities and teaching methods

Lecture, individual work and exercises on paper and on the computer, homework of statistical analysis of survey results


Assessment methods and criteria

Comprehensive written examination 80 %, homework 20 %


Comment

None


Recommended or required reading

Monka, Michael; Schönbeck, Nadine; Voß, Werner (2008): Statistik am PC. Lösungen mit Excel. München: Hanser Verlag.

Schira, Josef (2012): Statistische Methoden der VWL und BWL. Theorie und Praxis. München: Pearson Studium.

Bortz, Jürgen (2005): Statistik für Human- und Sozialwissenschaftler. Heidelberg: Springer Medizin Verlag.


Mode of delivery (face-to-face, distance learning)

Face-to-face