Forecasting for Business and Finance module (BU52023)

Learn how to use the RStudio application and the concept of time-series approaches with theory to create data visualizations and generating reports.

On this page
Credits

20

Module code

BU52023

You will combine the theory of forecasting with practical experience of using software used by researchers, data analysts, and statisticians for conducting data-driven tasks and analyses. This will allow you to help predict potential outcomes to different kinds of business and financial situations.

What you will learn

In this module, you will:

  • learn the basics of time-series econometrics
  • understand the theoretical foundations of forecasting models
  • explore how forecasting relates to key outcomes such as sales and revenue
  • learn how the industry uses RStudio as an Integrated Development Environment (IDE) for programming and data analysis

By the end of this module, you will be able to:

  • clean, manipulate, organise and visualise time-series data using RStudio
  • use these data for forecasting purposes
  • create data visualizations and generate reports

Assignments / assessment

Individual lab assignment (30%)

  • completed using RStudio within a 24-hour window

Group assignment (20%)

  • you will work within small groups to complete an assignment using RStudio

Final exam (50%)

  • completed within a 24-hour window

Teaching methods / timetable

You should expect weekly lectures for the theory based elements, lab sessions to use the RStudio application and recordings for you to watch as part of your independent study.

Week Topics covered
1 Introduction, Exploring Data Patterns, Time Series and their Components
2 Regression with Time Series Data
3 ARIMA and Box-Jenkins Methodology
4 Review

For this module, the exact dates of teaching and/or reading weeks are to be confirmed.

The module consists of lectures and computer lab sessions. Lectures focus on the theory behind time-series econometrics and forecasting methods.

Courses

This module is available on following courses: