Foundations of OR: Statistical Methods in OR: Forecasting in R
An introductory course to equip you with a tool bag of core quantitative forecasting techniques that are adaptable to almost any organisational setting. Appreciate the qualitative methods of forecasting by making use of expert opinion, judgement and scenarios.
Description
- Understand the process of making predictions based on past and present data.
- Learn about the most widely used short to medium term forecast methods and how they can be used in a variety of situations.
- Gain an insight as to why things can and do go wrong.
Learning objectives
- Appreciate the underlying assumptions of forecasting methods.
- Understand the importance of exploring the data before forecasting.
- Learn about the main characteristics of time series data.
- Identify data structures using a time (series) plot.
- Understand and implement smoothing techniques for forecasting time series with different structures, e.g., trend and cyclic behaviour such as seasonality.
- Learn the forecasting methods of moving average (MA), exponentially weighted moving average (EWMA) and extensions of EWMA for trend and seasonality.
Topics
- Basic forecasting principles
- The model building process
- Evaluate model accuracy
- Smoothing methods for forecasting
- Forecasting using regression
- Build and fit models for trend and/or seasonality
- The impact of context on forecasting
- Qualitative methods
- Forecasting longer term
Audience
For delegates that may have none or limited prior forecasting experience and need to make use of forecasts to be effective decision makers or organisational team players.
A pre-knowledge of basic statistics, particularly simple regression and the Normal distribution is desirable.
Course format
- PowerPoint presentation to introduce the topics
- Practical sessions using Minitab software and the Microsoft Excel analysis tool pack
- Group discussion/work to explore the topics in more detail
- Bring questions from your own work to embed your learning
- Supporting resource pack available to use following the course
Related courses
- Foundations of OR: Follow on to Forecasting: ARIMA modelling for forecasting
- Foundations of OR: Statistical Methods in OR: Multivariate Statistics