Content, progress and pedagogy of the module

The primary objective of the module is to teach basic statistical concepts and methods. The course is organized as an interaction between theoretical understanding and practical application. The course equips students with basic skills in data analysis which are required for analyzing socio-economic issues as well as learning more advanced methods in advanced semesters. In this regard, the course also teaches the use of a statistical program, R.

Upon the completion of this course students are expected to be able to investigate and interpret the basic statistical properties of any socio-economic data. Students should be able to formulate an appropriate hypothesis and test it using various statistical procedures. The students are expected to use various digital tools to report their analyses.

Learning objectives

Knowledge

The objective is that the student after the module possesses the necessary knowledge on:

• the statistical nature and properties of different variables when working with socio-economic data.
• basic probability and hypothesis testing.
• linear regressions.

Skills

The objective is that the student after the module possesses the necessary skills in:

• exploring real world data of socio-economic nature by exploring descriptive statistics.
• applying statistical techniques to calculate probabilities and find statistical evidence by performing hypotheses tests.
• estimating parameters of linear regression models and derive informed conclusions.

Competences

The objective is that the student after the module possesses the necessary competences in:

• identifying real world problems in the field of economics, and address those problems empirically by applying various statistical techniques.
• interpreting the results in an intuitive way and derive conclusions on the basis of statistical evidence.
• evaluating the applied approach and understand the limitations and shortcoming of statistical models and conclusions.

Type of instruction

For further information see §17.

Exam

Exams