This Analysing Data module at The Open University UK explores the fundamental statistical techniques and ideas used for analysing and interpreting data, covering models for data, estimation, confidence intervals, hypothesis testing and regression. 
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What you will study in the Analysing Data module at The Open University UK

The module will investigate a greater range of statistical techniques than those introduced at level 1, and will also provide a deeper understanding of the techniques that were introduced.

In this module you will explore the fundamental statistical techniques which can be used to analyse data to answer real, practical, questions such as ‘Does drug A work better than drug B?’ and ‘How often do major earthquakes occur?'.

The starting point for answering such questions is to model the variation in data: some of the most commonly used models for variation are considered in the first part of the module and some of their properties are investigated. 

The module then goes on to develop statistical techniques for using data and models of the variation to draw conclusions and answer questions of interest: the specific statistical techniques studied in the module include estimation, confidence intervals, hypothesis tests and regression.

An important skill for any statistician is the ability to communicate their statistical analysis clearly to others, both statisticians and non-statisticians. Statistical report writing is considered in one of the final units of the module.

In addition to the module texts, student learning is supported throughout by short video presentations, computer animations and online interactive practice quizzes.

Vocational relevance

The ability to analyse and interpret data is central to many careers in, for example, government, health, business, finance and market research. The material in this module explores the fundamental statistical techniques required for analysing and interpreting data. 

Statistical software packages are important data analysis tools for practising statisticians: the use of one such statistical software package is integral to this module. Another important skill required by practising statisticians, is the ability to communicate the results from their data analyses: this skill is developed through statistical report writing.

Detailed Programme Facts

  • Programme intensity Full-time
  • Credits
    30 alternative credits
  • Languages
    • English
  • Delivery mode
  • More information Go to the programme website

Programme Structure

  • You will learn

Successful study of this module should improve your skills in analysing and interpreting data.

  • Support from your tutor
You will have a tutor who will help you with the study material and mark and comment on your written work, and whom you can ask for advice and guidance. We may also be able to offer group tutorials or day schools that you are encouraged, but not obliged, to attend. Where your tutorials are held will depend on the distribution of students taking the module.

English Language Requirements

You need the following IELTS score:

  • Minimum required score:


    The IELTS – or the International English Language Test System – tests your English-language abilities (writing, listening, speaking, and reading) on a scale of 1.00–9.00. The minimum IELTS score requirement refers to which Overall Band Score you received, which is your combined average score. Read more about IELTS.

General Requirements

You need no pre-requisites to study this module, however you do need to be confident with mathematical notation and carrying out algebraic manipulation.

We also advise you are familiar with mathematical functions, including the logarithmic and the exponential functions. You’ll also use differentiation and integration; Analysing data will include some revision covering the specific techniques used.

Technological Requirements

A computing device with a browser and broadband internet access is required for this module. 


Check the programme website for information about funding options.

Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

Analysing Data
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