The course „Statistics“ discusses the following topics, presented in chapters:

Chapter 0: Prerequisities and basics

Chapter 1: Data, scales of measurement

Chapter 2: Descriptive statistics

Chapter 3: Estimating and testing proportions

Chapter 4: Expected value of quantitative variables

Chapter 5: Expectation comparison between two groups

Chapter 6: ANOVA

Chapter 7: Contingency tables

Chapter 8: Linear regression

In many areas of economics, such as marketing or financial markets, data is regularly collected and gathered to test theories about the underlying processes, such as hypotheses about consumers' purchasing decisions. This transformation of data into scientific theories is carried out using tools known as statistical methods. The course "Statistics" provides fundamental knowledge about statistical methods for analyzing univariate and multivariate datasets. Examples of such methods include estimating and testing proportions and expected values, analysis of variance, and linear regression models.

After successfully completing the course, students are able to independently select the appropriate statistical method for data related to a social or economic problem, perform quantitative analysis using results generated by statistical software, and interpret the findings.

The course design assumes continuous attendance and participation, which is why physical, emotional, and intellectual presence is expected in all sessions.

In sessions 5 and 10, attendance is mandatory because partial exams take place during these sessions. Only in justified exceptional cases (illness, death in the immediate family, etc.) is it possible to retake (at most) one of the partial exams at a later date.

Unexcused absence from the first session may, if necessary, lead to deregistration from the course and the allocation of the spot to someone on the waiting list.

Missing other sessions is tolerated; however, in case of absence, there is no possibility to earn points for the review questions or any bonus points (see also teaching/learning method(s)).

The schedule of the individual statistics courses follows a fixed timeline:

Sessions 1 - 4: Organizational matters, Chapters 0 - 4

Session 5: First partial test

Sessions 6 - 9: Chapters 5 - 8

Session 10: Second partial test

On Canvas, we provide learning paths, study clips, interactive applets, collections of exercises, practice exams, animations, and other materials to enable the students to work through the current material independently before each in-person session.

During the in-person sessions, the current material is reviewed and deepened, and there is an opportunity to ask questions and clarify uncertainties. An overview of the theoretical foundations is given, and the material is covered and practiced using concrete examples. Afterwards, review questions follow, which are to be answered individually via Canvas (using a laptop, tablet, smartphone, etc. that the students brought to this end) in the lecture hall.

Active participation by students in discussions and presentations is essential not only to learn statistical analysis methods but also to become familiar with statistical reasoning. For those interested, the learning platform also offers its own datasets and special learning videos to independently familiarize themselves with the statistical software R.

Participation in the review and bonus questions and earning possible bonus points through the questions posed during the in-person sessions is only allowed in attendance.

Two written partial tests: each with 10 questions, each question is worth 4 points.

The partial tests take place in sessions 5 and 10 of the course. Participants of the beAble program must contact their instructors regarding the need for disadvantage compensation no later than three weeks before the first exam date (5th session), i.e., possibly even before the course begins. If this deadline is not met, disadvantage compensation cannot be guaranteed. Please note that the disadvantage compensation is offered in a collective session and therefore does not necessarily coincide with the course dates.

Short review questions in sessions 2, 3, 4, 7, 8, and 9 of the course; a maximum of 20 points can be achieved in total (the worst result is dropped). Participation in the review questions is only possible in person.

Grading scheme:

Bonus points: Small amounts of additional points can be earned through achievements (participation in sessions, etc.) that go significantly beyond the essentials.

Prior completion of the Mathematics course is advisable. The content builds especially on sessions 5 and 6 of the Mathematics course. This knowledge is assumed, and it is recommended to independently acquire these contents using the materials from the Mathematics course.

The allocation of places during the registration period follows a "first come, first served" principle. After the registration period ends, the available course places are increased and allocated to people on the waiting list who do not yet have a valid registration for this study plan item in the current semester (i.e., exchange requests are not considered). This allocation is not based on the order on the waiting list but on urgency and study progress. The process is managed by the Vice-Rectorate for Teaching and Students and is therefore beyond the influence of the course instructor(s). Allocation criteria include whether students in the 2019 study plan version are already well advanced in their studies or whether students in the 2023 study plan version already have eligibility for courses from a study branch, are registered for at most one CBK credit point in the current semester, or are on the waiting list for this study plan item in the current semester.

For the allocation of places that become available after this assignment or possibly after the first session due to unexcused absences, the order on the waiting list is crucial. The instructors will inform about the respective procedure by email.

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Prior completion of the Mathematics course is advisable. The content especially builds on sessions 5 and 6 of the Mathematics course. This knowledge is assumed, and it is recommended to independently acquire these contents using the materials from the Mathematics course. The contents of the Mathematics course are available in the Open Course Mathematics (https://canvas.wu.ac.at/courses/4943, only available in German).