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Introduction to Inferential Statistics

Cristina Mitrea

Lucian Blaga University of Sibiu

Cristina Mitrea is an Associate Professor of Sociology. She earned her PhD in political science at Central European University.

Her research interests lie in the fields of political behaviour and political socialisation.


Course Dates and Times

Monday 7 ꟷ Friday 11 February 2022
2 hours of live teaching per day
10:00 ꟷ 12:00 CET

VIR: This is a virtual course

Prerequisite Knowledge

There is no prerequisite knowledge needed for this course beyond basic operations such as addition, subtraction, division and multiplication.

Short Outline

This course provides a highly interactive online teaching and learning environment, using state of the art online pedagogical tools. It is designed for a demanding audience (researchers, professional analysts, advanced students) and capped at a maximum of 16 participants so that the teaching team can cater to the specific needs of each individual.

Purpose of the course

Quantitative data is becoming increasingly available, and publications are making the use of it more prevalent in political science. This course offers you the necessary tools to engage in and become an informed consumer of quantitative research. The goal is to teach you basic inferential statistical techniques used in political science research, allowing you to progress to more advanced techniques.

ECTS Credits

3 credits Engage fully with class activities
4 credits Complete a post-class assignment

Long Course Outline

Day 1

The day begins with building blocks of statistical inference. We will discuss the relationship between populations and samples, issues of measurements and scale, types of variables, basic distributions (with a focus on the normal distribution), as well as measures of central tendency (mean, median, mode) and variability (range, variance and standard deviation).

Day 2

We continue to discuss normal distribution and the relationship between samples and populations, delving into the specifics of standardised scores and probability.

Day 3

We explore the logic of hypothesis testing. You will learn how to formulate and test simple hypotheses, touching on uncertainty and errors in testing.

Day 4

We progress to more complex hypothesis testing (t test and ANOVA) and explore comparisons to a given standard, comparisons between groups, and changes over time.

Day 5

We test relationships between variables using correlations, bivariate regression and the Chi-Square test. We discuss the principles behind these statistical techniques, the interpretation of results and assumptions. This session provides the foundation for multiple regression analysis.

How the course will work online

The course will be delivered using a combination of pre-class activities, live online interaction and post-class activities.

Before the course week, you will have access to readings and pre-recorded lectures which explain and clarify course material.

Daily live sessions will feature class discussions, Q&A, group exercises and tutorials on the application of statistical methods using freely available software such as web apps and spreadsheets.

Post-class activities include exercises that allow you to practice course material. The Instructor and Teaching Assistant will also be available for individual consultations to clarify course material, discuss research applications, and to offer other additional support.

Additional Information


This course description may be subject to subsequent adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc). Registered participants will be informed at the time of change.

By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, please contact us before registering.