MVZn5097 Introduction to linear models

Fakulta sociálních studií
jaro 2022

Předmět se v období jaro 2022 nevypisuje.

Rozsah
1/1/0. 7 kr. Ukončení: zk.
Vyučující
Zuzana Ringlerová, Ph.D. (přednášející)
Garance
Zuzana Ringlerová, Ph.D.
Katedra mezinárodních vztahů a evropských studií - Fakulta sociálních studií
Kontaktní osoba: Olga Cídlová, DiS.
Dodavatelské pracoviště: Katedra mezinárodních vztahů a evropských studií - Fakulta sociálních studií
Předpoklady
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Omezení zápisu do předmětu
Předmět je určen pouze studentům mateřských oborů.

Předmět si smí zapsat nejvýše 20 stud.
Momentální stav registrace a zápisu: zapsáno: 0/20, pouze zareg.: 0/20
Mateřské obory/plány
předmět má 11 mateřských oborů, zobrazit
Cíle předmětu
To provide students with a deep working understanding of linear regression models and several closely related variations.
To provide students with a strong foundation to enable future learning of other advanced statistical techniques, either in advanced courses, or independently.
To provide students with the skills needed to understand and critique research conducted using quantitative techniques.
To provide students with the skills needed to conceptualize, design, and conduct a rigorous quantitative research project, and write a paper based upon the results.
To provide working knowledge of how to analyze data using a statistical software.
Výstupy z učení
By the end of the course, students will be able to do the following:
- Understand of linear regression models and several closely related variations.
- Display a basic understanding of quantitative methods, which will enable future learning of other advanced statistical techniques.
- Demonstrate skills needed to understand and critique research conducted using quantitative techniques.
- Conceptualize, design, and conduct a rigorous quantitative research project, and write a paper based upon the results.
- Analyze data using a statistical software.
Osnova
  • 1) How do I set up my research to learn whether X causes Y?
  • 2) Getting to know my data
  • 3) Making inferences from a sample to the population
  • 4) Is my X related to Y? Bivariate regression
  • 5) What if I have more than one independent variable? Multiple regression
  • 6) Multiple regression. How do I interpret my model correctly?
  • 7) Including categorical variables
  • 8) Does my independent variable have the same effect under all circumstances? Interaction effects.
  • 9) What if the relationship between X and Y is not linear?
  • 10) Turning to the residuals. Assessing the homoskedasticity assumption and finding remedies.
  • 11) What if my observations are clustered?
  • 12) What to do if we suspect that Y causes X.
  • 13) What to do if the dependent variable is binary.
Literatura
    povinná literatura
  • WOOLDRIDGE, Jeffrey M. Introductory econometrics : a modern approach. Sixth edition. Boston: Cengage Learning, 2016. xxi, 789. ISBN 9781305270107. info
  • KELLSTEDT, Paul M. a Guy D. WHITTEN. The fundamentals of political science research. 2nd ed. Cambridge: Cambridge University Press, 2013. xxiv, 316. ISBN 9781107621664. info
Výukové metody
In this course, you will be learning new knowledge and skills in multiple ways:
You will learn theoretical concepts and practical skills from lectures and from the assigned readings.
You will reinforce the theoretical and practical skills by working on the homework assignments.
You will apply your knowledge and skills in writing your own research paper.
Metody hodnocení
Course requirements and grading:
Attendance 10%
Homework assignments 35%
Exams 30%
Research project 25%
Vyučovací jazyk
Angličtina
Informace učitele
If you have any questions about this course, do not hesitate to contact me at ringler@fss.muni.cz
Další komentáře
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