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Applied Statistics MSc/PGDip

Learn about the course below
Code
PGG311
Start
October 2022
September 2022: EU/INT induction
Duration
1 year full-time
2 years part-time
Attendance
Full-time
Part-time
Fees
£9,400 (UK) *
£14,500 (EU/INT) *
Course leader
Emma Ball
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Often known as the science of uncertainty, statistics is of vital importance in modern society where almost all sectors rely on the collection, analysis and interpretation of data. There is a great shortage of well qualified statisticians, data analysts and statistical consultants across the sector and this course has been specifically designed to meet that demand.

Why study MSc Applied Statistics at Middlesex University?

Applied statistics involves putting theory into practice - not only summarising and describing data, but extrapolating from it to draw conclusions about the population being studied. This is an applied, practically-orientated course that gives you advanced knowledge of statistical methods and the theory that underpins these methods. With a strong emphasis on relating theory to practice, you will develop your analytical, logical, numerical and problem-solving, skills that are in such high demand with employers.

Middlesex is one of only four institutions in the UK which has been approved as a mirror for the statistical programming language R – meaning you will have access to software used in the industry. You'll also learn how to use standard statistical software like SPSS and Minitab.

You'll have the freedom to choose the type of independent research project you do which can take the form of a theoretical dissertation, a survey or a more practical project involving a data set. If you're working, you'll have the option of basing your project at your workplace – making your studies even more relevant and beneficial for both you and your employer.

Course highlights

  • You will be able to work with real datasets by utilising our subscriptions to Bloomberg and Datastream
  • As a student of this course you'll receive a free electronic textbook for every module.

*Please note this course is subject to review.


Find out more

Sign up now to receive more information about studying at Middlesex University London.

What will you study on the MSc Applied Statistics?

You’ll gain a thorough understanding of mathematical and statistical concepts and techniques and how to apply them to data sets. You’ll develop an advanced knowledge of probability, distributions, inference and stochastic processes, statistical modelling and methods of analysis, and will work on highly technical problems both independently and as part of a team. You’ll learn how to obtain different types of data from a variety of sources, including electronic databases; analyse it using programming and computer packages; and compare and choose between different methods of modelling and analysis. The course also covers big data, and the use of both small samples and big data to make judgments about large populations.

  • Modules

    • Statistical Modelling (30 credits) - Compulsory

      This module aims to give students a solid grounding in some of the most important analysis methods. It looks at the different practices and assumptions made in different applied scientific disciplines. It provides students with an understanding of the empirical techniques commonly used in statistical analysis as well as the ability to use these techniques and critically evaluate and interpret empirical work.

    • Probability and Stochastic Processes (30 credits) - Compulsory

      This module aims to give students a solid grounding in some of the most important methods employed by statisticians by providing a deeper understanding of probability theory and random processes. Students will be introduced to modern topics and techniques in stochastic processes. They will learn the relevant theory and gain the ability to formulate and solve practical problems.

    • Inference Theory (15 credits) - Compulsory

      This module aims to introduce students to advanced techniques in inference theory. It develops students’ ability to understand statistical theory as well as applying it to computational methods. Students are introduced to a wide-range of advanced techniques in classical inference and are given a practical introduction to Bayesian analysis.

    • Descriptive Statistical Analysis (15 credits) - Compulsory

      On this module, students are taught the important concepts of descriptive statistical analysis applied on different types of data sets. The course will develop students’ appreciation of the task of a statistician for critically analysing data sets and will be useful to anyone considering a job in statistics. Students will develop a keener understanding about structures that underlie data observations.

    • Time Series and Forecasting (15 credits) - Compulsory

      Data obtained from observations collected sequentially over time are extremely common. The purpose of time series analysis is to understand or model the stochastic mechanism that gives rise to an observed series and to predict or forecast the future values of a series based on the history of that series, and, possibly, other related series or factors.

    • Data Mining (15 credits) - Optional

      The quantity of data available to analysts is growing at an ever-increasing rate. This data has become a vital tool for decision-making in a competitive world. However, the size, which makes the data so valuable, also makes it difficult to analyse using traditional statistical methods. This module introduces the student to a variety of methodologies now employed to explore, analyse, categorise and visualise data from large data sets.

    • Survival Analysis (15 credits) - Optional

      This module aims to introduce statistical methods used for modelling and evaluating survival data as well as to implement estimation and test procedures. Survival models are used in bio-statistical, epidemiological and health related fields, as well as in research in the physical sciences including economic, financial, sociological, psychological, political and anthropological data.

You can find more information about this course in the programme specification. Module and programme information is indicative and may be subject to change.

How will the MSc Applied Statistics be taught?

Lectures and talks by visiting speakers will introduce you to concepts and techniques, which you’ll explore further through workshops, seminars, and presentations and discussions in class. Case studies will help you to relate theory to practice, and we’ll encourage you to think critically; some of your work will be done in groups. You’ll supplement all this with your own independent reading and study, including the use of online resources.

Assessment

You’ll be assessed through exams, tests and your dissertation, as well as other individual and group coursework.

Changes for students in 2021

If you have travel restrictions to the UK due to coronavirus, this course can be started fully online with support to learn from your home country for the first term.

We are back on campus for the majority of teaching in Autumn 2021, as long as restrictions allow. Your timetable will be built around on campus sessions using our professional facilities, with online sessions for some activities where we know being virtual will add value. We’ll use technology to enhance all of your learning and give you access to online resources to use in your own time.

In case of any changes to government guidance, we‘ll be ready to move to teaching with more restrictions in place and continue to give you an excellent learning experience. In this scenario, on campus teaching should continue although more of your course will take place online.

The table below gives you an idea of what your learning will look like across a typical week. Some weeks might be different due to how we schedule classes and arrange on campus sessions.

This information may change slightly as we receive further guidance from the government. You’ll receive final arrangements for your teaching and a full course timetable before you start.

Scenario A: Without social distancing

Live in-person on campus learning

Contact hours per week, per level:

5 hours

Live online learning

Average hours per week, per level:

7 hours

Scenario B: With social distancing and/or with restrictions on travel to campus

Live in-person on campus learning

Contact hours per week, per level:

N/A

Live online learning

Average hours per week, per level:

12 hours

Outside of these hours, you’ll be expected to do independent study where you read, listen and reflect on other learning activities. This can include preparation for future classes. In a year, you’ll typically be expected to commit 1800 hours to your course across all styles of learning. If you are taking a placement, you might have some additional hours.

Read more about our scenarios for returning to campus and what they might mean for your teaching and learning experience, and how you’ll be able to access student support.

Future plans for teaching

We’re developing our plans for in-person on campus teaching following government advice to keep you safe. If more restrictions are put in place in the future, or there is another lockdown, we’ll deliver your learning and support fully online for a temporary period. We’ll make alternative arrangements for any required placements if they can’t go ahead as planned. We’ll always give you notice of any changes that we make.

Definitions of terms

  • Live in-person on campus learning – This will focus on active and experiential sessions that are both:
    • Led by your tutors including seminars, lab sessions and demonstrations We’ll schedule all of this for you
    • Student-led by you and other students, like small group work and presentations.
  • Live online learning – This will include lectures, tutorials and supervision sessions led by your tutor and timetabled by us. It also includes student-led group work that takes place online

  • Tutor set learning activities – This covers activities which will be set for you by your tutor, but which you will undertake in your own time. Examples of this include watching online materials, participating in an online discussion forum, completing a virtual laboratory or reading specific texts. You may be doing this by yourself of with your course mates depending on your course and assignments. Outside of these hours, you’ll also be expected to do further independent study where you’ll be expected to learn, prepare, revise and reflect in your own time.

Support

You’ll have a strong support network available to you to make sure you develop all the necessary academic skills you need to do well on your course.

Our support services will be delivered online and on campus and you’ll have access to a range of different resources so you can get the help you need, whether you’re studying at home or have the opportunity to come to campus.

You’ll have access to one to one and group sessions for personal learning and academic support from our library and IT teams, and our network of learning experts. Our teams will also be here to offer financial advice, and personal wellbeing, mental health and disability support.

More on teaching for your subject in 2021/22

Read our guide to what you can look forward to when you study your subject with us including more information about your teaching experience this autumn.

  1. Standard entry requirements
  2. International (inc. EU)
  3. How to apply
  1. UK
  2. EU fees
  3. EU/International
  4. Additional costs
  5. Scholarships and bursaries

How can the MSc Applied Statistics support your career?

There is a need in both the public and private sectors for well-qualified statisticians and this course will leave you ideally placed for a wide variety of employment opportunities in:

  • commerce
  • economics
  • accountancy
  • health sciences
  • natural and environmental sciences
  • computing
  • engineering
  • law
  • medical statistics
  • medical research
  • pharmaceutical industry

You might also wish to explore your options in research or academia, or even complete further study at doctoral level.

Statisticians work in many fields, from government to market research, measuring anything from changes in the environment revealing the effects of global warming to the effectiveness of medicines. There are a large number of employment opportunities for our graduates in medical statistics, medical research, commerce and industry, particularly the pharmaceutical industry. There are also many career opportunities both in areas directly related to statistics, such as economics and accountancy, and wider field in areas like health sciences, natural and environmental sciences, computing, engineering and law.


We’ll carefully manage any future changes to courses, or the support and other services available to you, if these are necessary because of things like changes to government health and safety advice, or any changes to the law.

Any decisions will be taken in line with both external advice and the University’s Regulations which include information on this.

Our priority will always be to maintain academic standards and quality so that your learning outcomes are not affected by any adjustments that we may have to make.

At all times we’ll aim to keep you well informed of how we may need to respond to changing circumstances, and about support that we’ll provide to you.

Other courses

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Duration: 1 year full-time, 2 years part-time

Code: PGG200

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