Introduction to modelling real phenomena from planning data collection or gathering observational data to analyzing and providing insights. Topics include experimental design from first principles and simulating the data generating process, linear regression and correlation, one- and two-way Analysis of Variance using open-source statistical software. Precludes additional credit for ECON 2202, ECON 2220, STAT 2509, STAT 2559, STAT 2602. Prerequisite(s): DATA 1517 or (STAT 1500 and STAT 2507) or (STAT 1500 and STAT 2655) or (STAT 1500 and STAT 3502); or permission of the Institute for Data Science. Lectures three hours a week, laboratory one hour a week.
Introduction to modelling real phenomena from planning data collection or gathering observational data to analyzing and providing insights. Topics include experimental design from first principles and simulating the data generating process, linear regression and correlation, one- and two-way Analysis of Variance using open-source statistical software. Precludes additional credit for ECON 2202, ECON 2220, STAT 2509, STAT 2559, STAT 2602. Prerequisite(s): DATA 1517 or (STAT 1500 and STAT 2507) or (STAT 1500 and STAT 2655) or (STAT 1500 and STAT 3502); or permission of the Institute for Data Science. Lectures three hours a week, laboratory one hour a week.
