This course will provide graduate students with the fundamental skills in experimental design and data analysis, with emphasis on the connection with management research. Concepts such as hypothesis testing (chi-square tests, t-tests), correlation, multiple regression, stepwise regression, analysis of variance (ANOVA), factorial experiments, blocking and confounding, and factor analysis will be discussed with a view to practical application. Students will use statistical software such as SPSS to enhance their understanding of the course material and gain experience with data analysis for management research. Weekly hours: 3 Lecture hoursPrerequisite(s): Undergraduate course in statistics or special permission.
This course will provide graduate students with the fundamental skills in experimental design and data analysis, with emphasis on the connection with management research. Concepts such as hypothesis testing (chi-square tests, t-tests), correlation, multiple regression, stepwise regression, analysis of variance (ANOVA), factorial experiments, blocking and confounding, and factor analysis will be discussed with a view to practical application. Students will use statistical software such as SPSS to enhance their understanding of the course material and gain experience with data analysis for management research. Weekly hours: 3 Lecture hoursPrerequisite(s): Undergraduate course in statistics or special permission.
