Prof. Dr. Christian Tröster - Teaching at KLU | KLU



Professor Christian Tröster, Assistant Professor of Leadership and Organizational Behavior


Teaching at KLU

Descriptive Statistics (BSc)

The vast amount of information that managers are confronted with poses a significant opportunity for decision-making quality. However, the increasing complexity of this data poses a serious challenge. In this course we will understand informed decision-making in business as a research process and statistics as a tool to reduce data complexity and inform decision-making.
The course follows the (business) research process: Defining the management problem, collecting data, data analysis, and reporting. The biggest part of the course will focus on basic concepts of statistics that are used to describe data and draw basic inferences about associations in the data. Emphasis will not be placed on memorizing formulas, but instead will be placed on applying statistics to real world business problems. Applications of the various concepts are covered through practical data analysis examples using the statistics software SPSS. At the completion of the course, the students will be able to use statistics to answer real world business problems. Students will also learn how to critically assess the quality of statistical analyses.

Introduction to Inference Statistics (BSc)

The vast amount of information that managers are confronted with poses a significant opportunity for decision-making quality. However, the increasing complexity of this data poses a serious challenge. In this course we will understand informed decision-making in business as a research process and statistics as a tool to reduce data complexity and inform decision-making.
The course follows the research process: Defining the management problem, collecting data, data analysis, and reporting. The biggest part of the course will focus on basic concepts of statistics that can be applied to analyze data in the field of business (but potentially also in other fields).  Emphasis will not be placed on memorizing formulas, but instead will be placed on applying statistics to real world business problems. Applications of the various concepts are covered through practical data analysis examples using the statistics software SPSS.
At the completion of the course, the students will be able to use statistics to answer real world business problems. Students will also learn how to critically assess the quality of statistical analyses.

Applied Statistics (MSc)

The vast amount of information that managers are confronted with poses a significant opportunity for decision-making quality. However, the increasing complexity of this data also poses a serious challenge. In this course we will understand informed decision-making in business as a research process and statistics as a tool to reduce data complexity, explore and test complex relationships between variables, and inform decision-making.
Students will learn how to test complex relationships between variables. Emphasis will not be placed on memorizing formulas, but instead will be placed on applying statistics to real world business problems. Thus, the course builds upon the students’ prior experience in statistics (i.e. the course Business Statistic and Econometrics). Applications of the various concepts are covered through practical data analysis examples using the statistics software SPSS, through cases, and quizzes.

Business Statistics and Econometrics (MSc)

The vast and increasing amount of information that managers are confronted with poses a significant opportunity for improving business performance. However, the increasing complexity of this data also poses a serious challenge. In this course we will understand informed decision-making in business as a research process and statistics as a tool to reduce data complexity, explore and test complex relationships between variables, and inform decision-making.
The course follows the (business) research process: Defining the management problem, collecting data, data analysis, and reporting. The course builds upon introductory courses in statistics and focuses on statistical inference and data reduction techniques and the application of statistical methods to real world business problems. Applications of the various concepts are covered through practical data analysis examples using the statistics software SPSS, through cases, and quizzes. An integral part of the course is a real world research project that students conduct in small groups.