MAS8407 : Practical Statistics for Exploratory Data Analytics
- Offered for Year: 2024/25
- Module Leader(s): Dr Clement Lee
- Lecturer: Mr Graham Cole
- Owning School: Mathematics, Statistics and Physics
- Teaching Location: Newcastle City Campus
Semesters
Your programme is made up of credits, the total differs on programme to programme.
Semester 1 Credit Value: | 20 |
ECTS Credits: | 10.0 |
European Credit Transfer System |
Aims
Statistical methods are of crucial for data science. This module aims to first introduce the fundamental statistical and mathematical concepts and techniques underpinning modern computational statistics and data analysis. Furthermore, this module aims to provide students with the basic skills needed for statistical modelling, data analysis and computing that ground these statistics concepts in a variety of business cases to make statistically sound conclusions and data driven decisions solve live commercial problems.
Outline Of Syllabus
- Data types
- Univariate data summaries (numerical and graphical)
- Fundamentals of probability theory
- Discrete and continuous probability models
- Probability model parameter estimation
- Confidence intervals and hypothesis tests
- Multivariate data summaries
- Principal components analysis (PCA)
- Unsupervised clustering techniques (k-means, hierarchical clustering)
- Linear regression (including variable selection) and regularisation
- Classification (logistic regression, discriminant analysis)
- R for data analysis and visualisation
Teaching Methods
Teaching Activities
Category | Activity | Number | Length | Student Hours | Comment |
---|---|---|---|---|---|
Scheduled Learning And Teaching Activities | Lecture | 6 | 2:00 | 12:00 | Hybrid (PiP/Zoom) lecture |
Structured Guided Learning | Lecture materials | 6 | 2:00 | 12:00 | Non synchronous on line - prerecorded lecture |
Guided Independent Study | Assessment preparation and completion | 2 | 10:00 | 20:00 | Formative Exercise |
Scheduled Learning And Teaching Activities | Practical | 11 | 2:00 | 22:00 | Present in Person Practical |
Guided Independent Study | Project work | 88 | 1:00 | 88:00 | Main Project |
Scheduled Learning And Teaching Activities | Drop-in/surgery | 11 | 2:00 | 22:00 | Present in Person Drop In |
Guided Independent Study | Independent study | 12 | 2:00 | 24:00 | Lecture follow-up/background reading |
Total | 200:00 |
Teaching Rationale And Relationship
Lectures will be used for the delivery and explanation of new methods, with a combination of pre-recorded asynchronous lectures, and hybrid synchronous lectures allowing the module to fulfil its blended learning role thereby allowing learners to join the sessions in a more flexible way.
Practical sessions allow learners to gain hands on experience with the tools and techniques described in the lectures, and to establish and test their understanding of the material and comfort in using it.
Drop-in sessions allow learners to receive additional support with the module materials in addition to the opportunities in the practical sessions.
Following up on lectures and revisiting the content is crucial to embedding understanding.
Assessment Methods
The format of resits will be determined by the Board of Examiners
Other Assessment
Description | Semester | When Set | Percentage | Comment |
---|---|---|---|---|
Report | 1 | M | 90 | Project report |
Oral Presentation | 1 | M | 10 | Recorded 5 minute presentation describing main findings |
Formative Assessments
Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.
Description | Semester | When Set | Comment |
---|---|---|---|
Report | 1 | M | A short technical report allowing learners to receive feedback on analytical techniques and report writing |
Report | 1 | M | A short technical report allowing learners to receive feedback on analytical techniques and report writing |
Assessment Rationale And Relationship
An extended technical report allows learners to fully explore the potential applications of the statistical techniques learned in the module, as well as providing them with the opportunity to generate useful insights from the data they are analysing. The video presentation showcases their communication skills as well as their ability to identify the main useful/interesting aspects of their analysis to discuss. Formative assignments allow learners to receive feedback on their analytical report writing and analysis technique before the full summative assessment.
Reading Lists
Timetable
- Timetable Website: www.ncl.ac.uk/timetable/
- MAS8407's Timetable