Course Objectives

• Become acquainted with the theoretical and practical elements of forecasting techniques and their applications.
• Acquire experience in analyzing a business problem using appropriate model for forecasting.
• Develop the skills to use the model for a problem solution and interpret for decision making.

UNIT I Overview

Overview of forecasting process – Forecasting, planning and goals – Forecasting data and methods

UNIT II Exploration

Exploratory Data Analytics - Time series graphics using R- Time series patterns- Scatterplots- Lag plots

UNIT III Models

Time Series Modeling using Regression– Forecasting using models– Evaluating the regression model

UNIT IV Methods

Time Series Decomposition – Components – Moving Averages – Classical method

UNIT V Advanced Techniques

Exponential smoothing- Trend methods- ARIMA models – Dynamic models- hierarchical or grouped time series.

Learning Resources

• Rob J Hyndman , George Athanasopoulos, Forecasting: Principles and Practice, Ed.2,2018, Otexts
• Devon Powers, On Trend: The Business of Forecasting the Future, Ed.1, 2019, University of Illinois Press
• Render, Quantitative Analysis For Management, Ed.13,2018, Pearson Education
• David Hendry , Jennifer Castle , Michael Clements, Forecasting: An Essential Introduction, Ed.1, 2019, Yale University
• Gerardus Blokdyk, Management And Forecasting A Complete Guide, Ed.1, 2019, 5STARCooks Press