Statistics

22B0753

Bachelor

English

5.0

winter- and summerterm

1 semester

This course is an intensive introduction to statistics aimed at preparing students for conducting a study in a real-world setting. The course provides the theoretical and technical details of various statistical methods, and serves as a tool to assist in all phases of the scientific process of statistical data analysis from data collection, via determining appropriate methods and statistical computing, to clearly communicating study outcomes.

1 Introduction to statistics
1.1   Key concepts
1.2   Qualitative and quantitative variables
1.3   Statistical software overview
1.4   Introduction to selected statistical software 

2 One-dimensional frequency distribution 
2.1   Empirical distribution function
2.2   Measures of location
2.3   Measures of scale
2.4   Graphical representation
2.5   Economic applications 

3 Two-dimensional frequency distribution
3.1   Two-dimensional frequency tables
3.2   Marginal and conditional distributions
3.3   Contingency tables
3.4   Measures of association
3.5   Economic applications 

4 Correlation and regression
4.1   Correlation analysis
4.2   Simple linear regression
4.3   Multiple linear regression
4.5   Economic applications 

5 Basics of probability theory
5.1   Key concepts
5.2   Conditional probability, independence and Bayes’ rule
5.3   Event trees
5.4   Economic applications 

6 Probability distributions
6.1   Probability distributions for discrete random variables
6.2   Probability distributions for continuous random variables
6.3   Economic applications 

7 Parameter estimation
7.1   Key concepts
7.2   Confidence intervals for the mean, proportion value and the variance
7.3   Economic applications 

8 Hypothesis testing
8.1   Key concepts
8.2   One-sample tests
8.3   Two-sample tests
8.4   Economic applications 

The total workload for the module is 150 hours (see also "ECTS credit points and grading").

• Written examination or
• Portfolio exam

PFP comprises a total of 100 points and consists of a homework assignment (HA) and a one-hour written examination (K1). Both elements are assigned 50 points.

Written examination: in accordance with the valid study regulations

Homework assignment as part of the PFP: approx. 15-20 pages

The requirements are specified in the respective lectures.

Arithmetic

Students distinguish the core areas of statistics. They can explain and illustrate the underlying ideas of specific methods and their principal areas of application. 

Students can justify the method selection, use software to do statistics, provide a comprehensive result interpretation, verify hypotheses, present the results, and summarize the outcomes in an integrative manner.

Students are able to critically reflect issues around the data.  They can critically evaluate the collected datasets, statistical methods and their outcomes. They can also discuss their outcomes through theoretical- and practice-relevant arguments.

Students are able to transfer their knowledge to real-world case studies including summary statistics calculation, uni- and bi-variate frequency analysis, simple and multiple regression analysis, basic forecast, event tree analysis, parameter estimation, hypothesis testing, interpretation and visualisation of results, and the use of appropriate statistical software.

Students are able to formulate research questions and hypotheses, select appropriate methodology, undertake research, handle data issues, solve statistical problems and present outcomes. They are able to justify their decisions by means of statistical methods and comprehensive analysis.

Students can present, visualise and communicate the analysis outcomes in oral presentations and in comprehensible written reports.

Students are able to critically reflect, question, and communicate the potential and limitations of statistical methods in applied analyses. They are aware of basic data protection issues.

This module prepares students for data-based further studies in any subject area.

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