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Linear Statistical Modelling, Short Course

  • Application Deadline
  • Unknown
University rank #501 (WUR) Milton Keynes, United Kingdom
The Linear Statistical Modelling programme offered by The Open University UK covers statistical modelling where a response variable depends on one or several explanatory variables: such as how well patients respond to a treatment, given their age and disease severity; or how different strains of wheat compare when grown in various conditions.  
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Taking a practical approach, you’ll use real problems and data to stimulate analyses and their interpretation. Statistical tools are introduced, and use of the statistical software package, GenStat (supplied) is taught. You need a reasonable understanding of basic statistical ideas, as developed by Analysing data. 

By studying the Linear Statistical Modelling programme is offered by The Open University UK, you’ll learn to use the most important methods of analysing data – a skill that too few people have.

What you will study

This module is about the statistical modelling of situations in which a response variable depends on at least one explanatory variable. It offers a practical treatment of an important area of statistical methodology, applicable in a wide variety of situations. For example, it enables us to deal with questions such as how cavity wall insulation will affect the total energy consumption of a house; or how the probability of a successful bone marrow transplant is influenced by the ages of the donor and recipient, and other factors; or how loss due to abrasion might depend on the hardness and tensile strength of samples of rubber.

Linear statistical modelling uses real problems and data to stimulate analyses and their interpretation. Technical background is not ignored, but the main emphasis is on the knowledge needed to analyse data effectively.

Detailed Programme Facts

  • Programme intensity Part-time
    • Part-time variant
  • Credits
    30 alternative credits
  • Languages
    • English
  • Delivery mode
    On Campus

Programme Structure

  • The module begins with a general introductory unit, including a review of the general statistical methods and concepts that will be used later. The next unit gives a complete introduction to using the statistics package Genstat for Windows (which is supplied). We then move on to the basic linear regression model, extensions of which are the core of this module.
  • Subsequent units introduce a wide variety of linear statistical modelling tools: one-way analysis of variance, multiple regression, more general analysis of variance and designed experiments. All these are widely applicable cases of the normal linear model.
  • Further units develop linear modelling in the more general framework of the generalised linear model: binary regression; the full generalised linear model; diagnostic checking; and log-linear modelling.
  • A closing unit applies the methods you have learnt to the analysis of further data sets.

English Language Requirements

This programme may require students to demonstrate proficiency in English.

General Requirements

You need no pre-requisites to study Linear statistical modelling. However, we recommend that you’re familiar with the following mathematical topics:

  • mathematical notation
  • following short algebraic arguments
  • handling the logarithmic and exponential functions
  • using formulae

We recommend you also have previous basic knowledge of statistical science; we’ll include some revision of the following topics:

  • histograms, boxplots and scatterplots
  • normal, Poisson and binomial distributions
  • the central limit theorem
  • confidence intervals
  • hypothesis testing
  • simple linear regression
  • correlation

We also recommend that you have some experience using a statistical software package.

Tuition Fee

Living costs for Milton Keynes

  • 848 - 1350 GBP/month
    Living Costs

The living costs include the total expenses per month, covering accommodation, public transportation, utilities (electricity, internet), books and groceries.


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