Syllabus

Title
0129 Quantitative Methods I
Instructors
Jana Hlavinova, Ph.D., Assoz.Prof. PD Dr. Zehra Eksi-Altay, BSc.MSc.
Contact details
jana.hlavinova@wu.ac.at, zehra.eksi@wu.ac.at
Type
VUE
Weekly hours
2
Language of instruction
Englisch
Registration
10/03/25 to 10/05/25
Registration via LPIS
Notes to the course
Subject(s) Bachelor Programs
Quantitative Methods I
Dates
Day Date Time Room
Wednesday 10/15/25 08:00 AM - 10:00 AM TC.0.04
Wednesday 10/15/25 11:30 AM - 12:30 PM TC.5.05
Wednesday 10/22/25 08:00 AM - 10:00 AM TC.0.04
Wednesday 10/22/25 11:30 AM - 12:30 PM TC.5.05
Friday 10/24/25 08:00 AM - 09:30 AM TC.0.10 Audimax
Wednesday 10/29/25 08:00 AM - 10:00 AM TC.0.04
Wednesday 10/29/25 11:30 AM - 12:30 PM TC.5.05
Wednesday 11/05/25 08:00 AM - 10:00 AM TC.0.04
Wednesday 11/12/25 08:00 AM - 10:00 AM TC.0.04
Wednesday 11/12/25 11:30 AM - 12:30 PM TC.5.05
Friday 11/21/25 08:00 AM - 10:00 AM TC.0.10 Audimax
Wednesday 12/03/25 08:00 AM - 10:00 AM TC.0.04
Wednesday 12/03/25 11:30 AM - 12:30 PM TC.5.05
Wednesday 12/10/25 08:00 AM - 10:00 AM TC.0.04
Wednesday 12/10/25 11:30 AM - 12:30 PM TC.5.05
Wednesday 12/17/25 08:00 AM - 10:00 AM TC.0.04
Wednesday 12/17/25 11:30 AM - 12:30 PM TC.5.05
Friday 01/09/26 11:00 AM - 01:30 PM TC.0.10 Audimax

On this page:

to top
Contents

 

Course contents:

  • introduction to the open source programming environment R, R as a calculator, named vectors in R
  • functions of one variable, defining and evaluating functions in R
  • special functions and their properties: linear, quadratic, polynomial, power, exponential, logarithmic
  • concatenation and composition of functions, inverse of functions
  • graphs of functions, graphing functions in R
  • brief introduction to functions of several variables
  • elementary matrix algebra and its usage in R
  • systems of linear equations and their representation using matrix algebra
  • analytical and numerical differentiation
  • integration
  • single and multivariable optimization
  • elementary financial mathematics (discounting and compounding, simple annuities): computation and visualization using R
  • analytical and numerical rootfinding
to top
Learning outcomes

After completing the course, students should be familiar with basic concepts, methods and tools in mathematics and computing that are necessary for the quantitative analysis of problems in modern business and economics. Moreover, students will have acquired basic programming skills in the open-source computer language R, enabling them to independently conduct simple mathematical analyses.

to top
Attendance requirements

The attendance and participation in all lectures and practical sessions is strongly recommended. Attendance will be checked in the practical sessions, two absences (no matter whether excused or not) are allowed.

The participation in the in-class assignments in the practical sessions (see details below) is only allowed in presence, no retake possibility in case of absence.

to top
Teaching/learning method(s)

The course will be taught as a lecture accompanied by practicals in small groups (VUE). There will be 8 on-campus lectures with 120 participants. Concerning the practicals, there will be 7 on-campus sessions, starting with the first week (the day of the first main lecture). The main focus of the practical sessions will be to cover the relevant R material and gain computational skills. Please make sure to always bring your computer with R installed to the practical session; this will be necessary to work on the in-class assignments. Additionally,  in order to support students for R programming, regular tutorials will be offered by the tutors.

Students are expected to be active in the class. We also encourage the use of the central forum.

to top
Assessment
Course evaluation consists of four parts:
  1. Entry exam (15 points) - On campus, will take place on October 24, 2025
  2. Midterm exam (30 points) - On campus, will take place on November 21, 2025
  3. Final exam (40 points) - On campus, will take place on January 9, 2026
  4. 7 in-class assignments (15 points in total) - will take place in each practical session
    • In-class assignments will be assessed as individual work
    • Throughout the course, there will be a total of 7 assignments, each worth 3 points. At the end of the course, we take min(15, S) points as the result for this part, where S is the overall score. This means that missing up to two sessions still allows to achieve the full 15 points for this part of assessment.

The following grading scale applies:

  • 89.00-100.00 - Excellent (1)
  • 78.00-88.99 - Good (2)
  • 67.00-77.99 - Satisfactory (3)
  • 56.00-66.99 -  Sufficient (4)
  • 0.00-55.99 -  Insufficient (5)

 

to top
Readings

Please log in with your WU account to use all functionalities of read!t. For off-campus access to our licensed electronic resources, remember to activate your VPN connection connection. In case you encounter any technical problems or have questions regarding read!t, please feel free to contact the library at readinglists@wu.ac.at.

to top
Recommended previous knowledge and skills

Mathematical skills and knowledge at high school level.

Last edited: 2025-07-04



Back