Sorry! De informatie die je zoekt, is enkel beschikbaar in het Engels.
This programme is saved into My study choice.
This programme cannot be saved.
You are not logged in yet to My study choice Portal. Login or create an account to save your programmes.
Something went wrong, try again later.

Multivariate Data Analysis Business & Manag. Res.

In this course, students will learn to evaluate the quality of quantitative data, gain insight into the strengths and limitations of various multivariate analysis techniques, learn how to perform analysis using R and how to interpret and communicate its output.

Hester van Herk

Hester van Herk

Hester van Herk is professor of Cross-Cultural Marketing Research at VU and Adjunct Senior Research Fellow at the University of Western Australia in Perth. Hester holds a PhD (2000) in marketing and cross-cultural psychology from Tilburg University. She studied psychology at Leiden University with a major in research methodology and minors in social and organizational psychology and in mathematics. After obtaining her MSc, she worked as a scientific researcher at Statistics Netherlands, Solvay Duphar, ABN Amro, and MarketResponse. At Vrije Universiteit Amsterdam she was Program Director of the Bachelor of Business Administration (2010-2013) and Acting Department Chair at the Marketing department (2013-2015).

Course Description

This course will emphasize understanding, implementation, and interpretation of multivariate statistical methods. The course will involve both lecture and lab work. First, we discuss how to analyze and deal with missing data. Second, the course will focus on multivariate techniques such as analysis of (co)variance and regression analysis including moderation and mediation. Third, you will learn some more advanced techniques using latent variables and apply confirmatory factor analysis to multi-item scales. You will be introduced to structural equation modeling (SEM). You will learn to analyze SEM models and assess their fit. Lastly, multi-level analysis is learned.
This course prepares the student for analyzing datasets using the freely available programming language R. R is a platform for which many scholars write packages. The basis enables you to manipulate data, clean data, and test hypotheses. The packages enable you to use advanced methods such as structural equation modeling. You will learn how to read various datasets into R, how to create and change variables, and how to
conduct manipulations such as recoding data.

Study Characteristics

  • Study period: February  2022 – March 2022 (Period 4)
  • Credits: 5 ECTS
  • Tuition fee: €1250 (20% discount for early bird registration)
  • Registration deadline: 24-01-2022 (early bird registration: 03-01-2022)
  • Course Description & Study Characteristics

    Course Description

    This course will emphasize understanding, implementation, and interpretation of multivariate statistical methods. The course will involve both lecture and lab work. First, we discuss how to analyze and deal with missing data. Second, the course will focus on multivariate techniques such as analysis of (co)variance and regression analysis including moderation and mediation. Third, you will learn some more advanced techniques using latent variables and apply confirmatory factor analysis to multi-item scales. You will be introduced to structural equation modeling (SEM). You will learn to analyze SEM models and assess their fit. Lastly, multi-level analysis is learned.
    This course prepares the student for analyzing datasets using the freely available programming language R. R is a platform for which many scholars write packages. The basis enables you to manipulate data, clean data, and test hypotheses. The packages enable you to use advanced methods such as structural equation modeling. You will learn how to read various datasets into R, how to create and change variables, and how to
    conduct manipulations such as recoding data.

    Study Characteristics

    • Study period: February  2022 – March 2022 (Period 4)
    • Credits: 5 ECTS
    • Tuition fee: €1250 (20% discount for early bird registration)
    • Registration deadline: 24-01-2022 (early bird registration: 03-01-2022)

Would you like to register or want to know more?

Please register with the Apply Now button at the top of this page. For more info please contact the course coordinator prof. dr. Hester van Herk: