Course ObjectiveIn 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.
Course ContentEconomics 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.
Method of AssessmentExam with open questions - individual assessment
Two digital exams - individual assessment
Weakly surprise question - individual assessment
LiteratureDoane, David P. and Lori E. Seward (2015/2019), Applied Statistics in
Business & Economics, fifth/sixth edition, McGraw-Hill
Supplementary documents via Canvas
Additional InformationFor this course we use the Stata software. This program is available on
the computers on the campus of the university.
Recommended background knowledgeQuantitative Research Methods I
|Language of Tuition||English|
|Faculty||School of Business and Economics|
|Course Coordinator||dr. G.J. Franx|
|Examiner||dr. J.M. Sneek|
You need to register for this course yourself
|Teaching Methods||Lecture, Instruction course, Computer lab|
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