Forecasting is a structured approach to predict future outcomes by examining past data and trends. It employs data analysis tools to offer crucial insights for decision making, strategic planning, and resource distribution. This is vital to foresee market changes, refine operations, and make informed choices critical for staying competitive in the business arena. This course equips participants with tools to create accurate forecasts, handle data variability, and maintain forecast precision. Each module is paired with a computer lab to provide practical experience with the forecasting methods covered. Additionally, the course features real-world case studies and discussions to assist you in: using time series analysis methods, assuming that future patterns will resemble past relationships; assessing the causation and correlation between variables for regression analysis; combining various forecasts to develop a unified forecast; and generating forecasts using software packages. These concepts will be applied to a real-world case as the class project. Weekly hours: 2.5 Lecture hours and .5 Seminar/Discussion hoursPermission of the department required. Prerequisite(s): COMM 207.3.
Forecasting is a structured approach to predict future outcomes by examining past data and trends. It employs data analysis tools to offer crucial insights for decision making, strategic planning, and resource distribution. This is vital to foresee market changes, refine operations, and make informed choices critical for staying competitive in the business arena. This course equips participants with tools to create accurate forecasts, handle data variability, and maintain forecast precision. Each module is paired with a computer lab to provide practical experience with the forecasting methods covered. Additionally, the course features real-world case studies and discussions to assist you in: using time series analysis methods, assuming that future patterns will resemble past relationships; assessing the causation and correlation between variables for regression analysis; combining various forecasts to develop a unified forecast; and generating forecasts using software packages. These concepts will be applied to a real-world case as the class project. Weekly hours: 2.5 Lecture hours and .5 Seminar/Discussion hoursPermission of the department required. Prerequisite(s): COMM 207.3.
