040195 KU Data Analysis on Organization and Personnel (MA) (2022W)

Summary: This course introduces students to multivariate statistics for analyzing data in human resources, economics, and related disciplines.
The aim of this course is to provide participants with an understanding of the quantitative research process from hypotheses development to testing the hypotheses with the appropriate statistical methods.

Goal: Upon completion of the course, participants should be able to conduct their own study and analyses data sets with a variety of statistical methods. Discussed topics include:

• Developing and testing hypotheses
• Introduction to univariate and multivariate methods
• Analysis of variance
• Regression analysis

The emphasis is on empirical applications and the mathematics of econometric will be introduced only as needed.

Goal: Upon completion of the course, students will be able to undertake regression analysis and inference on a variety of hypotheses involving cross-sectional and time series data.
This course introduces students to regression tools for analyzing data in economics, finance and related disciplines. Extensions include regression with discrete random variables, instrumental variables regression, quasi-experiments, and regression with time series data. The objective of the course is for the student to learn how to conduct – and how to critique – empirical studies in economics, finance and related fields. Accordingly, the emphasis of the course is on empirical applications. The mathematics of econometrics will be introduced only as needed and will not be a central focus.

Summary: “This course emphasizes statistical methods for analyzing data used by social scientists. Topics include simple and multiple regression analyses and the various methods of detecting and correcting data problems.”Goal: Upon completion of the course, students will be able to undertake regression analysis and inference on a variety of hypotheses involving cross-sectional and time series data.This course introduces students to regression tools for analyzing data in economics, finance and related disciplines. Extensions include regression with discrete random variables, instrumental variables regression, quasi-experiments, and regression with time series data. The objective of the course is for the student to learn how to conduct – and how to critique – empirical studies in economics, finance and related fields. Accordingly, the emphasis of the course is on empirical applications. The mathematics of econometrics will be introduced only as needed and will not be a central focus.