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Regression Analysis, an Intensive Course (RSS1.01) - Confirmed

Regression analysis is the most important quantitative technique to master. It’s essential for every big data, statistical, and causal inference technique broadly used in social science. This one-week summer course reviews everything from basics to advanced topics, building a solid foundation in applied regression analysis. 



    The application deadline has passed, applying is no longer possible

    This one-week summer course is suitable for beginners, those interested in advanced techniques, and people looking to solidify their foundation in regression.

    Regression is historically the most applied analytical approach in quantitative social science. Today, it may appear to be falling out of fashion as causal inference is displacing correlational approaches, big data techniques ditch inferential methods, and more advanced tools take center stage, but nothing could be further from the truth. Every popular causal inferential approach uses regression at its foundation; machine learning is built on regressions, and advanced tools are usually just regression with fancy modifications. 

    To truly master these approaches, a sound foundation of regression analysis is essential to develop comprehensive knowledge, making your learning (life) infinitely easier. Additionally, regression analysis remains the tool of choice for many areas of social science, from econometrics to survey-based public opinion research. 

    This one-week summer course offers a speedy review of regression foundations and ventures into advanced topics, offering a jumping board to the multitude of advanced techniques.


    Starting date

    17 June 2024, 9 am
    Educational method
    Main Language
    17 June 2024, 9 am - 21 June 2024, 5 pm
    Levente Littvay
    Unique code


    Type of education
    Entry requirements
    See the requirements in cost and admission
    Study load (ECTS)
    Radboud Summer School

    Startdate: 17 June 2024, 9 am - 21 June 2024, 5 pm
    ECTS credits: 2 ECTS. For more information see credits and certificate.

    Course programme

    After reviewing linear regression, we turn to the assumptions made when conducting regression analysis. This includes discussions of regression’s use and misuse along with talking through practical considerations in social science quantitative research broadly. 

    Then we cover advanced topics like:

    1. Non-continuous dependent variables (e.g. binary and ordered logistic and probit regressions, Poisson and negative binomial regression, and multinominal models).
    2. Dealing with sampling issues and data clustering. 
    3. Missing data treatments. 

    Finally, we review how to use regression to think about mediation and moderation. In the end, participants will be ready to conduct state-of-the-art statistical data analysis suited for academia and industry.

    Total package & social events

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    Levente Littvay

    Levente Littvay

    Levente Littvay is a Research Professor at HUN-REN Centre for Social Sciences and Senior Research Fellow at the Democracy Institute of Central European University, where he also was (Full) Professor of Political Science (2007-2023) and taught graduate courses in research design, applied statistics, electoral politics, voting behavior, political psychology, and American politics and was the inaugural and only two-time recipient of the university's Teaching Award (2015 for methods-, and 2021 for online teaching). 

    Littvay received his MA and PhD in Political Science and an MS in Survey Research and Methodology from the University of Nebraska-Lincoln. Taught numerous research methods workshops globally, such as at Waseda University in Tokyo, Japan, Bamberg University in Germany, and the University of Geneve in Switzerland among others. 

    He is the founder and Academic Coordinator of MethodsNET, a Presidium member of the Hungarian Political Science Association, and head of Team Survey in Team Populism. He was a member of the European Social Survey’s Round 10 (2020-21) democracy and COVID-19 module questionnaire design teams and Co-Principal Investigator for the Comparative Study of Election Systems for Hungary and Tunisia. 

    His awards include the European University Institute’s Fernand Braudel Senior Research Fellowship (2019-20), the 2022 Giovanni Sartori Prize for best paper in the Italian Political Science Review / Rivista Italiana di Scienza Politica, and the Morton Deutsch Award for the best 2017 article in Social Justice Research. His books include Multilevel Structural Equation Modeling with Bruno Castanho Silva and Constantin Manuel Bosancianu in SAGE’s QASS (little green book) series, which was also published in Mandarin Chinese.

    The application deadline has passed, applying is no longer possible



    • Regular: €1049 (application deadline 13th of May)
    • Student & PhD's: €699 (application deadline 13th of May)

    Includes: your course, short morning and late afternoon courses, coffee and tea during breaks, a warm lunch every day, Official Opening, MethodsNET Café (including some drinks and snacks) Official Closing (with some drinks and snacks) and a 1-year (2024 calendar year) free membership as MethodsNET regular member.

    Excludes: transport, accommodation, social events and other costs. 

    Discounts and Scholarships


    Level of participant 

    • Master
    • PhD
    • Postdoc
    • Professional

    Admission requirements:  

    If you want to learn regression analysis or venture into more advanced topics and need a solid review, this course is for you. If you are a total beginner with inferential statistics, you can still do this course, but be ready to work very hard. If these topics scare you, this class is not for you. It is too intensive. For those without any foundations in statistics, I will also offer an online course (at no extra charge) that you can use to catch up. Please set aside a few hours every day for the two weeks before the course if you think you may need this. I do not recommend trying to binge it in just a day or two.

    Admission documents: 


    Cannot join us this year? 

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