MGMTMSA 437
Forecasting and Time Series
Management-Master of Science in Business Analytics · 2 units · Graduate professional courses (400-499)
Limited to Master of Science in Business Analytics students. Covers principal methods of time series data analysis and forecasting that are applicable in many functional areas of business, including simple and multiple regression, seasonal decomposition, AutoRegressive Integrated Moving Average (ARIMA), vector autoregressive, dynamic linear, error correction models. Use of R, RStudio and its various packages for regression and time series econometrics analysis and forecasting models.
S/U or letter grading.
Requisites
UCLA lists no requisites for this course.
Requires
Everything that has to come before this course, not just the courses named in the requisite above.
Nothing — this is an entry point.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
No course in the catalog lists this as a requisite.