Course

Course Summary
Credit Type:
Course
ACE ID:
STAT-0021
Organization's ID:
#510
Organization:
Statistics.com
Location:
Online
Length:
8 weeks (120 hours)
Dates Offered:
Credit Recommendation & Competencies
Level Credits (SH) Subject
Upper-Division Baccalaureate 3 forecasting analytics
Description

Objective:

The course objective is introduce on the most popular business forecasting methods: regression models, smoothing methods including Moving Average (MA) and Exponential Smoothing, and Autoregressive (AR) models. It also discusses enhancements such as second-layer models and ensembles, and various issues encountered in practice.

Learning Outcomes:

  • visualize time series data
  • Understand the different components of time series data
  • Distinguish explanation from forecasting
  • Specify appropriate metrics to assess forecasting models
  • Use smoothing methods with time series data
  • Adjust for seasonality
  • Use regression methods for forecasting
  • Account for autocorrelation
  • distinguish real trend and patterns from random behavior.
  • choose an appropriate time series forecasting method
  • Fit the appropriate time series model
  • Evaluate performance
  • use the model for forecasting

General Topics:

  • Characterizing Time Series and the Forecasting Goal
  • Evaluating Predictive Accuracy and Data Partitioning
  • Smoothing-based Methods
  • Regression-based Models
  • Forecasting in Practice
Instruction & Assessment

Instructional Strategies:

  • Audio Visual Materials
  • Classroom Exercise
  • Coaching/Mentoring
  • Computer Based Training
  • Discussion
  • Practical Exercises
  • Project-based Instruction

Methods of Assessment:

  • Other
  • Quizzes
  • Written Papers
  • Project

Minimum Passing Score:

80%
Supplemental Materials