We have to deal with statistics and probabilities every day. Is a certain drug effectively curing headache? How long, on average, do I wait for the subway? Can women drive better than men? And, of course, statistical methods are also key in business and economics and an essential tool that everybody active in these fields should know about. Does a new web design attract more buyers than the old one? How many clients should a company survey to obtain reliable evidence about the interests of their entire clientele? What is the average household income in Germany? Which country has a particular high income inequality? Does it take less than X months, on average, for an unemployed person to find a new job?
This course offers an introduction to statistical methods that you can use to i) describe and plot data, ii) plan a data collection project, iii) derive general statements from data samples, iv) analyze random processes, and v) analyze big data sets by means of machine learning algorithms.
Since an increasing number of jobs in both the private sector and economic research requires knowledge about how to handle data for empirical analyses, this course does also cover the practical implementation of statistical methods using the software R.
Students who successfully master this course, are able to i) describe data sets using appropriate measures, ii) select appropriate types of plots to visualize data sets, iii) estimate distribution parameters, iv) conduct and interpret statistical hypothesis tests, v) use inductive statistics as a foundation for their empirical work and to critically reflect about statistical results in general, vi) explain the basic functioning of selected machine learning algorithms, and vii) to implement the discussed methods using the software R.
The course consists of lectures (2 SWS) and exercise sessions (2 SWS). In addition, there is a weekly office hour for R-related questions offered by a student assistant.
We regularly teach this course in the winter semester. The course language is English. The course is mandatory in the first semester of our new B.Sc. IBS/IES programs.
The course is worth 5 ECTS which can be earned by passing a written exam (90 minutes, single-choice format). Students can improve their grade by successfully participating in six quizzes during the semester.
To accompany the lecture we use the following textbook:
- Newbold, P., W. L. Carlson, and B. M. Thorne (2019), Statistics for Business and Economics – Global Edition, 9th edition, Pearson.
All information about the course is summarized in the syllabus (version for winter term 2022/23).
You can find exams from previous years on this website. Feel free to use them for preparing for your exam.
Basic Math Skills
The FAU faculty of science offers a StudOn website that allows students to recapitulate mathematical concepts that you should know from high school. We recommend to use this website to check if you master these basics of mathematics. In the case that you don’t, the website offers also a range of training exercises that you can use to practice and to refresh your knowledge.
Alternatively, we recommend that students follow the (online) math refresher-course that is offered for new IES and IBS students before the semester.