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Applied statistical modelling

What do wage rates depend on? How many medals is a nation predicted to win at the next Olympics? Can we predict an OU student’s exam score based on their age and which qualification they’re studying? You can explore questions like these using the statistical modelling techniques in this module. It takes a practical approach with an emphasis on the fitting of models and the interpretation of results. Also, depending on your interests, you’ll study topics related to econometrics (statistics applied to economics) or data science.

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OU qualifications are modular in structure; the credits from this undergraduate module could count towards a certificate of higher education, diploma of higher education, foundation degree or honours degree.

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Module

Module code
M348
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
Across the UK, there are two parallel frameworks for higher education qualifications, the Framework for Higher Education Qualifications in England, Northern Ireland and Wales (FHEQ) and the Scottish Credit and Qualifications Framework (SCQF). These define a hierarchy of levels and describe the achievement expected at each level. The information provided shows how OU module levels correspond to these frameworks.
OU SCQF FHEQ
3 10 6
Study method
Distance Learning
Module cost
See Module registration
Entry requirements
See Entry requirements

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What you will study

Applied statistical modelling (M348) will develop your general statistical modelling skills beyond that delivered by Analysing Data (M248). In this module, simple linear regression is extended to model a wide variety of dataset types.

Book 1: Linear models
You’ll start with a revision of simple linear regression, combined with an introduction to the statistical software used, namely R. Initially, simple linear regression will be extended in two separate ways: firstly, by including more than one continuous explanatory variable, and secondly to deal with situations when the explanatory variable is categorical. You’ll then see how these two extensions can be combined to form regression models with any number of variables, continuous or categorical. You’ll then finish this book by putting the modelling techniques you’ve learned so far into practice by building a statistical model to predict success at the Olympics. In doing so, you’ll discover how fitting a model is only one part of using data to answer a question.

Book 2: Generalised linear models
All models you consider in Book 1 assume that the response variable is continuous and can be modelled, possibly after transformation, using a normal distribution. Although this is often sufficient for data analysis, there are situations where it is not. So, in Book 2, you’ll consider how linear models can be extended to cope with such situations. The resulting models are known as generalised linear models.

You’ll see that it’s possible to have models where the response distribution used is a binomial distribution instead of a normal distribution. You’ll then see that it’s possible to use other distributions as well, such as the Poisson distribution or the exponential distribution. Finally, in this book, you’ll see how a particular form of generalised linear model, the loglinear model, can be used to explore relationships between categorical variables. The loglinear model is particularly helpful when contingency tables relate to data with three or more categorical variables.

Book 3: Applications
Having extended the range of ‘regression’ tools in your data analysis toolbox, Book 3 focuses on two specialist applications of statistics: econometrics and data science. You’ll study only one of these.

In the econometrics strand, you’ll see how the assumptions associated with linear models can be problematic when applied to economic data. For example, data may represent observations made over time, so they’re not independent. In this strand, you’ll see how econometricians deal with such problems.

The data science strand focuses on a couple of topics of particular interest to data scientists. Firstly, you’ll focus on finding clusters in data: groups of observations that are similar to one another but different to observations in other groups. Next, you’ll learn suitable techniques for grouping the data when we don’t have examples of any groups – or even know how many groups there should be! You’ll then consider the challenges that ‘big data’ bring and discuss what can be done to address some of these challenges.

You’ll finish with a unit that will pull the content in the module together and help you prepare for the end-of-module assessment.

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 vital skill required by practising statisticians is communicating the results from their data analyses. You’ll develop this skill through statistical report writing.

Teaching and assessment

Support from your tutor

Throughout your module studies, you’ll get help and support from your assigned module tutor. They’ll help you by:

  • Marking your assignments (TMAs) and providing detailed feedback for you to improve.
  • Guiding you to additional learning resources.
  • Providing individual guidance, whether that’s for general study skills or specific module content.
  • Facilitating online discussions between your fellow students, in the dedicated module and tutor group forums.

Module tutors also run online tutorials throughout the module. Where possible, recordings of online tutorials will be made available to students. While these tutorials won’t be compulsory for you to complete the module, you’re strongly encouraged to take part.

Assessment

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

Future availability

Applied statistical modelling​ (M348) starts once a year – in October.

This page describes the module that will start in October 2023.

We expect it to start for the last time in October 2029.

Regulations

As a student of The Open University, you should be aware of the content of the academic regulations which are available on our Student Policies and Regulations website.

    Course work includes:

    6 Tutor-marked assignments (TMAs)
    End-of-module assessment
    No residential school


    Entry requirements

    There is no formal pre-requisite study, but you must have the required mathematical and statistical skills.

    Check you’re ready for M348 and see the topics it covers.

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

    Preparatory work

    We recommend you have some experience using statistical software such as Minitab or SPSS. Analysing Data (M248) and an OU level 2 mathematics module will be ideal preparation.

    Register

    Start End Fee
    - - -

    No current presentation - see Future availability

    This module is expected to start for the last time in October 2029.

    Additional Costs

    Study costs

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

    If your income is not more than £25,000 or you are in receipt of a qualifying benefit, 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, Mastercard, Visa 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).


    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 2023. Fees normally increase annually in line with inflation and the University's strategic approach to fees. 

    This information was provided on 02/12/2022.

    Can you study an Access module for free?

    In order to qualify you must:

    1. be resident in England
    2. have a personal income of less than £25,000 (or receive qualifying benefits)
    3. have not completed one year or more on any full-time undergraduate programme at FHEQ level 4 or above, or completed 30 credits or more of OU study

    How to apply to study an Access module for free

    Once you've started the registration process , either online or over the phone, we'll contact you about your payment options. This will include instructions on how you can apply to study for free if you are eligible.

    If you're unsure if you meet the criteria to study for free, you can check with one of our friendly advisers on +44 (0)300 303 0069 or you can request a call back.

    Not eligible to study for free?

    Don't worry! We offer a choice of flexible ways to help spread the cost of your Access module. The most popular options include:

    • monthly payments through OUSBA
    • part-time tuition fee loan (you'll need to be registered on a qualification for this option)

    To explore all the options available to you, visit Fees and Funding.

    What's included

    You’ll have access to a module website, which includes:

    • a week-by-week study planner
    • course-specific module materials, including activities using the module software
    • video content
    • assessment details, instructions and guidance
    • online tutorial access
    • access to student and tutor group forums.

    You’ll be provided with printed books covering the module content, including explanations, examples and activities to aid your understanding of the concepts and associated skills and techniques. You’ll also receive a printed module handbook.

    You will need

    A scientific calculator may be helpful.

    Computing requirements

    You’ll need broadband internet access and a desktop or laptop computer with an up-to-date version of Windows (10 or 11), or macOS (11 'Big Sur' or higher).

    Any additional software will be provided or is generally freely available.

    To join in spoken conversations in tutorials, we recommend a wired headset (headphones/earphones with a built-in microphone).

    Our module websites comply with web standards, and any modern browser is suitable for most activities.

    Our OU Study mobile app will operate on all current, supported versions of Android and iOS. It’s not available on Kindle.

    It’s also possible to access some module materials on a mobile phone, tablet device or Chromebook. However, as you may be asked to install additional software or use certain applications, you’ll also require a desktop or laptop as described above.

    If you have a disability

    The OU strives to make all aspects of study accessible to everyone and this Accessibility Statement outlines what studying M348 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 Disability support website.