What will I learn on this module?
The aim of this module is to provide you with the knowledge and practical skills for understanding the statistical methods and programming for data science. The module combines both theoretical and practical approaches so that you will have the skills to tackle problems in various realistic business settings. It also equip you with programming skills in R for effective and efficient statistical data analysis.
This module is primarily concerned with examining and analysing data using R (statistical programming) arising from real world environments (e.g., businesses, industries) and to relate the extracted information to strategic, tactical and operational decision-making. You will covers topics such as:
• Introduction to statistical modelling, data processing and big data and to challenges in practical data analyses
• Fundamental statistics: variable types: nominal, ordinal, categorical. Formulae: functions, powers, summation
• Introduction to R programming language environment
• Introduction to practical data analysis with the statistical software environment R for data manipulation, sampling, importing and exporting data and for drawing Scatterplot, Histogram, etc.
• Application and implementation of core statistical analysis using R (e.g., probability and distributions, Statistical models (e.g., Linear models, Generalized linear models, Nonlinear least squares and maximum likelihood models)
• How to subsume and to present results of statistical data analyses (for statisticians and non-statisticians)
• Practical statistical analysis of real data sets, reporting and presentation of the obtained results
How will I learn on this module?
The module includes a combination of methods to support learning, including lectures and computer assisted seminars allowing you to put the theory from lectures into practice. Topics will normally be introduced in lectures and explored through real world examples and practical exercises (helping you develop the knowledge and understanding needed) and guided learning activities. You will be encouraged to develop independent learning skills to explore further in the subject area and take benefit from Northumbria University’s Enterprise Data Analytic Clinic and Institute of coding.
How will I be supported academically on this module?
You will be given advice and feedback on your work and progress during the timetabled classes. In addition, the eLP (electronic learning portal module) blackboard is used to provide extensive support materials.
What will I be expected to read on this module?
All modules at Northumbria include a range of reading materials that students are expected to engage with. Online reading lists (provided after enrolment) give you access to your reading material for your modules. The Library works in partnership with your module tutors to ensure you have access to the material that you need.
What will I be expected to achieve?
Knowledge & Understanding:
1. Demonstrate deep knowledge and practical skills for understanding the statistical methods and techniques for data science
2. Critically assess application of adequate techniques for understanding and exploring business data and how it can be exploited for decision making with programming in R
Intellectual / Professional skills & abilities:
3. Appraise and Apply different statistical methods and techniques to real world business environment having to deal with and exploit huge volumes of data using R programming environment
4. Evaluate and reflect on solving real life business problems using suitable statistical techniques based on critical review of relevant literature
Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
5. Build a critical awareness of professional, legal, cultural and ethical issues surrounding analysis, exploration and dissemination of data
How will I be assessed?
Formative assessment: Exercises provided and carried out within practical classes and workshops will build up to form a basis of the summative assessment. Feedback will be given during these practical classes and workshops and/or through discussions via email/blackboard forum.
Summative assessments: A written assignment (4000 words) comprising analysis of given data by using appropriate statistical techniques with programming in R for understanding and exploring business data and solving business decision problems, recognising and appreciating opportunities for innovation (100%) and will test MLOs 1, 2, 3, 4 and 5.
Feedback: You will be given detailed feedback on the assignment clearly identifying both the weaknesses and strong points of the work.
Pre-requisite(s)
None
Co-requisite(s)
None
Module abstract
The aim of this module is to provide you with the knowledge and practical skills for understanding the statistical methods and programming for data science. The module combines both theoretical and practical approaches so that you will have the skills to tackle problems in various realistic business settings. It equips you with programming skills in R for effective, efficient statistical data analysis. This module includes a combination of methods to support learning, including lectures and computer assisted seminars allowing you to put the theory from lectures into practice. Topics will normally be introduced in lectures and explored through real world examples and practical exercises (helping you develop the knowledge and understanding needed) and guided self-learning activities. You will be encouraged to develop independent learning skills to explore further in the subject area.
Course info
Credits 20
Level of Study Postgraduate
Mode of Study 1 year Full Time
Department Computer and Information Sciences
Location City Campus, Northumbria University
City Newcastle
Start September 2025
All information is accurate at the time of sharing.
Full time Courses are primarily delivered via on-campus face to face learning but could include elements of online learning. Most courses run as planned and as promoted on our website and via our marketing materials, but if there are any substantial changes (as determined by the Competition and Markets Authority) to a course or there is the potential that course may be withdrawn, we will notify all affected applicants as soon as possible with advice and guidance regarding their options. It is also important to be aware that optional modules listed on course pages may be subject to change depending on uptake numbers each year.
Contact time is subject to increase or decrease in line with possible restrictions imposed by the government or the University in the interest of maintaining the health and safety and wellbeing of students, staff, and visitors if this is deemed necessary in future.
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