Description
Advanced statistics builds upon the fundamental principles of intermediate statistics and further explores complex relationships between variables and conducting sophisticated modeling. These techniques allow researchers to uncover deeper insights, identify patterns, and make predictions. Advanced statistical methods have diverse applications across disciplines. This course will provide the strategies necessary to analyze and extract insights. Techniques such as data mining, time series analysis, and spatial statistics have emerged to address the unique challenges posed by big data. Upon completion of this course, students will be able to apply regression models to interpret the relationship between one dependent variable and multiple independent variables; formulate hypothesis testing; assess multivariate techniques; and evaluate machine learning algorithms within the realm of advanced statistics. Prerequisite: PSY 601, Intermediate Statistics (or) equivalency with a letter grade of ‘C’ or better