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Linear statistical modelling

This module 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. 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 (M248). You’ll learn to use the most important methods of analysing data – a skill that too few people have.

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Module

Module code
M346
Credits

Credits

  • Credits measure the student workload required for the successful completion of a module or qualification.
  • One credit represents about 10 hours of study over the duration of the course.
  • You are awarded credits after you have successfully completed a module.
  • For example, if you study a 60-credit module and successfully pass it, you will be awarded 60 credits.
30
Study level
3
Study method
Distance Learning
Module cost
See Module registration
Entry requirements
See Am I ready?

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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.

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.

The Genstat package is extensively used throughout the module to perform the necessary calculations and analyses.

You will learn

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

Professional recognition

This module may help you to gain membership of the Institute of Mathematics and its Applications (IMA). For further information, see the IMA website.

This module may also help you to apply for the professional award of Graduate Statistician conferred by The Royal Statistical Society (RSS).

Teaching and assessment

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.

Contact us if you want to know more about study with The Open University before you register.

Assessment

The assessment details for this module can be found in the facts box above.

You can choose whether to submit your tutor-marked assignments (TMAs) on paper or online through the eTMA system. You may want to use the eTMA system for some of your assignments but submit on paper for others. This is entirely your choice.

Future availability

Linear statistical modelling starts once a year – in October. This page describes the module that will start in October 2018. We expect it to start for the last time in October 2021.

Regulations

As a student of The Open University, you should be aware of the content of the academic regulations which are available on our Essential Documents website.

    Course work includes:

    6 Tutor-marked assignments (TMAs)
    Examination
    No residential school

    Course satisfaction survey

    See the satisfaction survey results for this course.


    Entry 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.

    Check you’re ready to study Linear statistical modelling with our self-assessed quiz.

    Talk to an advisor if you’re still not sure if you’re ready.

    Preparatory work

    Analysing data (M248) teaches the statistical science knowledge we recommend you to have before starting Linear statistical modelling. In addition, the mathematical competence level required to study Analysing data successfully is similar to the level we recommend to study this module. Analysing data also exposes you to a statistical software package.

    Register

    Start End England fee Register
    06 Oct 2018 Jun 2019 £1464.00

    Registration closes 13/09/18 (places subject to availability)

    Register
    This module is expected to start for the last time in October 2021.

    Additional Costs

    Study costs

    There may be extra costs on top of the tuition fee, such as a laptop, travel to tutorials, set books and internet access.

    If you're on a low income you might be eligible for help with some of these costs after your module has started.

    Ways to pay for this module

    Open University Student Budget Account

    The Open University Student Budget Accounts Ltd (OUSBA) offers a convenient 'pay as you go' option to pay your OU fees, which is a secure, quick and easy way to pay. Please note that The Open University works exclusively with OUSBA and is not able to offer you credit facilities from any other provider. All credit is subject to status and proof that you can afford the repayments.

    You pay the OU through OUSBA in one of the following ways:

    • Register now, pay later – OUSBA pays your module fee direct to the OU. You then repay OUSBA interest-free and in full just before your module starts. 0% APR representative. This option could give you the extra time you may need to secure the funding to repay OUSBA.
    • Pay by instalments – OUSBA calculates your monthly fee and number of instalments based on the cost of the module you are studying. APR 5.1% representative.

    Joint loan applications

    If you feel you would be unable to obtain an OUSBA loan on your own due to credit history or affordability issues, OUSBA offers the option to apply for a joint loan application with a third party. For example, your husband, wife, partner, parent, sibling or friend. In such cases, OUSBA will be required to carry out additional affordability checks separately and/or collectively for both joint applicants who will be jointly and severally liable for loan repayments.

    As additional affordability checks are required when processing joint loan applications, unfortunately, an instant decision cannot be given. On average the processing time for a joint loan application is five working days from receipt of the required documentation.

    Read more about Open University Student Budget Accounts (OUSBA).  

    Employer sponsorship

    Studying with The Open University can boost your employability. OU courses are recognised and respected by employers for their excellence and the commitment they take to complete. They also value the skills that students learn and can apply in the workplace.

    More than one in ten OU students are sponsored by their employer, and over 30,000 employers have used the OU to develop staff so far. If the module you’ve chosen is geared towards your job or developing your career, you could approach your employer to see if they will sponsor you by paying some or all of the fees. 

    • Your employer just needs to complete a simple form to confirm how much they will be paying and we will invoice them.
    • You won’t need to get your employer to complete the form until after you’ve chosen your module.  

    Credit/debit card

    You can pay part or all of your tuition fees upfront with a debit or credit card when you register for each module. 

    We accept American Express, Maestro (UK only), Mastercard, Visa/Delta and Visa Electron. 

    Mixed payments

    We know that sometimes you may want to combine payment options. For example, you may wish to pay part of your tuition fee with a debit card and pay the remainder in instalments through an Open University Student Budget Account (OUSBA).

    For more information about combining payment options, speak to an adviser.


    Please note: your permanent address/domicile will affect your fee status and therefore the fees you are charged and any financial support available to you. The fees and funding information provided here is valid for modules starting before 31 July 2019. Fees normally increase annually in line with inflation and the University's strategic approach to fees. 

    This information was provided on 21/06/2018.

    What's included

    Module books, website, and online forums.

    You will need

    Calculator (basic mathematical functions would be useful).

    You require access to the internet at least once a week during the module to download some essential module resources and to keep up to date with module news.

    Computing requirements

    A computing device with a browser and broadband internet access is required for this module. Any modern browser will be suitable for most computer activities. Functionality may be limited on mobile devices.

    Any additional software will be provided, or is generally freely available. However, some activities may have more specific requirements. For this reason, you will need to be able to install and run additional software on a device that meets the requirements below.

    A desktop or laptop computer with either:

    • Windows 7 or higher

    The screen of the device must have a resolution of at least 1024 pixels horizontally and 768 pixels vertically.

    To participate in our online-discussion area you will need both a microphone and speakers/headphones.

    Our Skills for OU study website has further information including computing skills for study, computer security, acquiring a computer and Microsoft software offers for students.

    If you have a disability

    The OU strives to make all aspects of study accessible to everyone and this Accessibility Statement outlines what studying M346 involves. You should use this information to inform your study preparations and any discussions with us about how we can meet your needs.

    To find out more about what kind of support and adjustments might be available, contact us or visit our Overcoming barriers to study if you have a disability or health condition website.