• Anwendung von Erlerntem in einem internationalen Umfeld.
• Kennen der Wachstumsprinzipien in einem anderen ökonomischen und kulturellen Umfeld.
• Konkretes Üben und Anwenden von interkulturellen Fähigkeiten der Studierenden.

• explain the framework of statistical reasoning.
• judge the benefits and limits of statistical methods and conclusions.
• summarize the results and conclusions of statistical analyses in a precise way.
• select statistical procedures according to given situations and questions.
• apply standard techniques in new situations and adapt the procedures.
• appraise the content and the limits of statistical analyses in publications.

Lecture Series ''Testing and Estimating''

• represent the distributions of random variables graphically.
• calculate moments of random variables and interpret them in a given context.
• explain the framework of testing hypotheses and estimating parameters.
• apply basic testing and estimating procedures and generalize the conclusions correctly.
• criticize the assumptions of basic testing and estimating procedures.
• derive the minimal sample size for basic testing and estimating procedures.

Lecture Series ''Multiple Linear Regression''

• apply the ordinary least squares method to derive estimators.
• analyze and compare the statistical properties of estimators.
• explain the classical linear model assumptions.
• run the calculations of a multiple linear regression for toy examples with small data sets by hand.
• interpret the software outputs of multiple linear regression for application examples in the given context.
• use model diagnostics to check the assumptions and to judge the quality of adapted models.
• apply inference procedures in multiple linear regression models.
• compare the advantages and disadvantages of different inference procedures.
• construct testing procedures for multiple linear constraints in multiple linear regression models.
• apply specification techniques to improve the quality of models.
• apply selection techniques to choose appropriate models.

Die Studierenden erarbeiten die gestellten Aufgaben selbstständig und setzen sie individuell um, und verstehen bzw. verorten Architekturtheoretisches und bautechnisches Wissen.
• Sie führen eine eigenständige Literaturrecherche durch und wenden die nötigen Baunormen und das bautechnische Wissen an.
• Sie kommunizieren die Komplexität ihrer Projektarbeit am Computer, in Planform und Modell sowie in Sprache und Schrift verständlich.
• Sie erkennen situationsbedingte sowie aufgabenrelevante Sachverhalte und wenden das in der theoretische Vorlesung Wissen an
• Sie bewerten die Leistung von anderen Studierenden und ordnen die eigene Leistung ein.

• explain the framework of statistical reasoning.
• judge the benefits and limits of statistical methods and conclusions.
• summarize the results and conclusions of statistical analyses in a precise way.
• select statistical procedures according to given situations and questions.
• apply standard techniques in new situations and adapt the procedures.
• appraise the content and the limits of statistical analyses in publications.

Lecture Series ''Testing and Estimating''

• represent the distributions of random variables graphically.
• calculate moments of random variables and interpret them in a given context.
• explain the framework of testing hypotheses and estimating parameters.
• apply basic testing and estimating procedures and generalize the conclusions correctly.
• criticize the assumptions of basic testing and estimating procedures.
• derive the minimal sample size for basic testing and estimating procedures.

Lecture Series ''Multiple Linear Regression''

• apply the ordinary least squares method to derive estimators.
• analyze and compare the statistical properties of estimators.
• explain the classical linear model assumptions.
• run the calculations of a multiple linear regression for toy examples with small data sets by hand.
• interpret the software outputs of multiple linear regression for application examples in the given context.
• use model diagnostics to check the assumptions and to judge the quality of adapted models.
• apply inference procedures in multiple linear regression models.
• compare the advantages and disadvantages of different inference procedures.
• construct testing procedures for multiple linear constraints in multiple linear regression models.
• apply specification techniques to improve the quality of models.
• apply selection techniques to choose appropriate models.

• Kreativität im Finden und der Ausgestaltung von Forschungslücken.
• Ausdauer und Durchhaltevermögen in der Ausarbeitung von Forschungsthemen.

Interaktion mit Befragten bei wissenschaftlichen Untersuchungen