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Programme & Unit Catalogues

MA30234: Statistics for business II

[Page last updated: 03 August 2022]

Academic Year: 2022/23
Owning Department/School: Department of Mathematical Sciences
Credits: 6 [equivalent to 12 CATS credits]
Notional Study Hours: 120
Level: Honours (FHEQ level 6)
Semester 1
Assessment Summary: CW 100%
Assessment Detail:
  • Coursework (CW 100%)
Supplementary Assessment:
Like-for-like reassessment (where allowed by programme regulations)
Requisites: Before taking this module you must take MA20228
Learning Outcomes: Students should be able to set up and analyse regression models and assess the resulting model critically. They should be able to model temporal data, and to provide forecasts with associated uncertainty estimates. They should be able to use the R statistical programming language to perform analyses.

Aims: This course provides the methods for analysing regression data and time series data. Both types of data arise frequently in business applications, and the course will emphasis applications in this area.
Aims - To teach the methods of analysis appropriate for simple and multiple regression models. To introduce techniques for modelling and forecasting time series.

Skills: Statistical skills (taught and assessed).

Content: Simple and multiple regression: estimation of model parameters, tests, confidence and prediction intervals, residual and diagnostic plots. Practical forecasting. Time plot. Trend-and-seasonal models. Exponential smoothing. Holt's linear trend model and Holt-Winters seasonal forecasting. Autoregressive models. Box-Jenkins ARIMA forecasting.

Programme availability:

MA30234 is Optional on the following programmes:

School of Management
  • UMMN-ANB07 : BSc(Hons) Business with Thin sandwich placement(s) (Year 3)


  • This unit catalogue is applicable for the 2022/23 academic year only. Students continuing their studies into 2023/24 and beyond should not assume that this unit will be available in future years in the format displayed here for 2022/23.
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