STAT 348
Predictive Analytics
Statistics
College of Physical and Mathematical Sciences
Course Description
Prepare for Exam SRM and CAS's Exam MAS-I. Understand the basics of several important analytical tools including regression models, generalized linear models, regression trees, time series models, principal component analysis and clustering. Use these models to estimate parameters, determine importance of key variables, perform model selection, perform prediction, and understand key characteristics of the data.
When Taught
Fall
Grade Rule
Standard Grade Rule: A B C D E I
Fixed
3
Fixed
3
Fixed
0
Title
Basics of Statistical Learning
Learning Outcome
Perform exploratory analysis and understand how to choose what type of model to use for particular characteristics of the data and the context of a specific business problem
Title
Generalized Linear Models
Learning Outcome
Understand generalized linear models and how to select distributions and link functions. Estimate parameters, perform diagnostic tests, interpret model output, and perform prediction
Title
Time Series Models
Learning Outcome
Understand basic concepts of stochastic processes. Describe and use common time series models.
Title
Decision Trees
Learning Outcome
Explain, interpret, and use regression trees for regression and classification
Title
Principal Component Analysis
Learning Outcome
Calculate and interpret principal components for a data set
Title
Cluster Analysis
Learning Outcome
Cluster observations using K-means and hierarchical clustering
