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Applied Statistical Methods (ASM)


Business processes have to be monitored and understood if they are to be controlled and the usual way of doing this is to collect (often numerical) information about them.  Unfortunately, all human activity is to a greater or lesser extent subject to randomness and this complicates understanding and decision making.  Statistics is the science of collecting data, describing and presenting it, understanding and quantifying randomness present in it, finding facts from it and making informed decisions on the basis of it.  This module covers the general concepts and techniques of statistics that apply to industrial and commercial disciplines and shows how these methods may be applied to specific problems.  The philosophy of the module is to concentrate on the concepts and applications of statistical processes, rather than the mathematical theory behind them.


Upon successful completion participants will be able to:

  • Demonstrate a comprehensive understanding of the nature and significance of variation and evaluate its occurrence in practical situations.

  • Independently interpret and evaluate data analysis situations to enable the appropriate selection and implementation of a range of statistical techniques.

  • Develop hypotheses that may be successfully analysed using appropriate statistical techniques; implement these analyses and interpret the outcome in a practical problem-solving situation.

  • Recognise when additional, more complex analytical techniques are required to address unpredictable situations of data-based problem solving.


  • Basic Parameters (Descriptive Statistics & Probability)
  • Distributions: e.g. Binomial, Poisson, Exponential and Normal.
  • Exploratory Data Analysis (EDA)
  • Sampling & Significance Testing.
  • Goodness of Fit testing.
  • Analysis of Variance (ANOVA)
  • Correlation & Regression Analysis.
  • Design of Experiments (DoE).
  • Distribution-free (non-parametric) statistics.
  • Contingency Tables
  • Statistics on the computer.


4,000 words (100% weighting)


1 week