Study Guide

Learning outcomes

To understand basic concepts of quantitative research. To be able to use basic quantitative data analysis methods and interpret analysis results.

Implementation and methods of teaching

Contact lessons on campus, data analysis assignments

Timing and attendance

Contact lessons on campus according to the timetable.

Learning material and recommended literature

Lecture material given by the teacher.

Exam retakes

Course exam on the last lessons.
Reexam dates annouced at the beginning of the course.

Learning environment

Contact lessons and Moodle

Student time use and work load

2 cr = 54 hours of student work: lectures 26 hours + self-studying and practicing

Contents

Basic statistical concepts. Sampling. Measurement. Descriptive analysis: transformations, tables, graphs. Numerical descriptive measures: measures of central tendency, variation and shape. Statistical relationships: correlation, cross tabs. One sample tests. Repeated measurements, changes. Comparing groups.

Assessment criteria

Exam graded 0-5

Assessment scale

1-5

Assessment criteria: level 1 (assessment scale 1–5)

1 = Student understands the basic concepts of quantitative research and remembers their definitions. Student is able to use basic descriptive methods in analysing research data and read the respective research results.

Assessment criteria: level 3 (assessment scale 1–5)

3 = Student understands the basic concepts quantitative research and is able to explain them. Student is able to use basic descriptive methods and statistical testing methods in analysing research data and interpret the respective results.

Assessment criteria: level 5 (assessment scale 1–5)

5 = Student masters and is able to use of the basic concepts of quantitative research fluently. Student is able to justify the selection and use all the statistical analysis methods on the course. Student masters the interpretation of the respective analysis results as well as understands their practical implications.