The Business Forecasting module of the Business Analysis course

Goal: Learn to build forecasting models and evaluate their quality.

Methods:

Short-term forecasting: simple average method, moving average method, exponential smoothing method; medium-term forecasting: Brown's method, Holt's method, Winters' additive and multiplicative methods; Long-Term Forecasting: Additive and Multiplicative Decomposition Methods

Forecast Quality Assessment: SSE, MAD, MAPE, MPE, MaxAD, MaxAPE, R², …

Autocorrelation Analysis and ARIMA Models

Linear Regression Analysis /applied to Stationary and Dynamic Data/

Time Series Analytics: Forecast Error Analysis, Outlier Analysis of Time Series Data, Intervention Analysis, Relationship Analysis, Spectral Analysis

Upon completion of this module, the participant will be able to:

Identify the data required to build forecasting models

Build forecasts based on identifying trends and seasonality in data

Evaluate the Quality of Forecasts

Quantitatively evaluate Seasonality

Quantitatively assess the impact of factors on the forecast value

Please note that:

This module is available in both open and corporate formats.