KL7012 - Statistical Programming

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. The reading list for this module can be found at: http://readinglists.northumbria.ac.uk

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

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):
5. Build a critical awareness of 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 (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)

An undergraduate degree with major in computing and information sciences or mathematical and statistical disciplines with applied computing components

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 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, Institute of coding.

Course info

Credits 20

Mode of Study 2 years full-time with Advanced Practice
3 other options available

Department Computer and Information Sciences

Location City Campus, Northumbria University

City Newcastle

Start September 2023

Data Science MSc

All information is accurate at the time of sharing.

Full time Courses starting in 2023 are primarily delivered via on-campus face to face learning but may include elements of online learning. We continue to monitor government and local authority guidance in relation to Covid-19 and we are ready and able to flex accordingly to ensure the health and safety of our students and staff.

Contact time is subject to increase or decrease in line with additional restrictions imposed by the government or the University in the interest of maintaining the health and safety and wellbeing of students, staff, and visitors, potentially to a full online offer, should further restrictions be deemed necessary in future. Our online activity will be delivered through Blackboard Ultra, enabling collaboration, connection and engagement with materials and people.

Current, Relevant and Inspiring

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Fees and Funding
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