Quantitative Research Methods II

Vrije Universiteit Amsterdam

Course Description

  • Course Name

    Quantitative Research Methods II

  • Host University

    Vrije Universiteit Amsterdam

  • Location

    Amsterdam, The Netherlands

  • Area of Study

    Research Methodology

  • Language Level

    Taught In English

  • Course Level Recommendations


    ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

    Hours & Credits

  • ECTS Credits

  • Recommended U.S. Semester Credits
  • Recommended U.S. Quarter Units
  • Overview

    In this course you will learn about several important statistical and econometrical topics and several quantitative techniques that are
    relevant and often used in Economics and Business Economics (Academic and Research Skills). These techniques are not only relevant in an academic context, but also help in solving concrete practical economic and business economic problems (Bridging Theory and Practice - Knowledge). You will not only learn the techniques, but also learn how to abstract from a practical problem in the real world to a statistical problem, and back from a statistical solution to a solution that is relevant for the real world (Academic and Research Skills).

    After successfully completing this course, the student can:
    • properly use statistical notation (both passively and actively);
    • calculate elementary probabilities;
    • model events with the Bernoulli distribution, the binomial, uniform and normal distribution;
    • calculate and interpret descriptive statistics (mean, median, variance, correlation coefficient, skewness, proportion, etc.);
    • use the concepts population, sample and sample variation;
    • calculate confidence intervals (for mean, proportion and variance);
    • distinguish statistical and practical significance;
    • perform one sample tests (for mean, median, proportion and variance);
    • perform two sample test (for mean, median, proportion and variance);
    • create contingency tables and perform a chi-square test;
    • perform multiple regression (including tests, confidence intervals, dummy’s, interaction and residual analysis);
    • choose the right test for a given problem;
    • visualize data and relationships;
    • using Stata for the above topics.

    After successfully completing this course the student is able:
    • to read and write texts in which statistics occurs;
    • can use standard software for solving statistical problems.

    Economics is a scientific discipline in which quantitative data are very important. Theoretical considerations of the effect of minimum wages on unemployment, or the effect of bonuses on the performance of employees are useful, but the final test is not the theory but confrontation with practical data. Unfortunately such data are rarely if ever completely unambiguous. Business cycles go up one day, and go down the other day, and usually there are more factors to cause noise in the data. Statistics provides means to draw reliable conclusions from data. The modern economist must therefore be able to handle statistics and to handle statistical software to visualize data. In this course such
    skills are taught: using Stata statistical analyses are carried out, connected to theoretical topics.

    Computer tutorials

    Exam with open questions - individual assessment
    Two digital exams - individual assessment
    Weakly surprise question - individual assessment

    Quantitative Research Methods I

Course Disclaimer

Courses and course hours of instruction are subject to change.

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