KC5001 - Applied Statistical Methods

You will learn on this module via a combination of lectures and laboratory sessions involving the use of appropriate statistical software. Classes will be scheduled in our modern computer laboratories enabling you to apply the techniques presented in the lecture part of the session and, in this way, gain an understanding of the material and use software as appropriate to solve problems. The bespoke laboratory sessions will take place broadly every other week.

Assessment involves an assignment and a laboratory examination. You will receive both written and oral feedback from the assignment. Oral feedback will be given concurrently during the laboratory sessions. Further to this, you will also receive exam feedback after the end of semester exam, particularly relevant if you are considering further statistical modules at Level 6.

Your ability to solve problems based on case studies using appropriate statistical techniques will be assessed via an individual assignment with individualised data, and your ability to construct logical multistep solutions and to critically evaluate your findings for a range of problems will be tested in a laboratory exam at the end of the module.

In addition, we operate an open door policy where you can meet with your module tutor to seek further advice or help if required.

You will be supported academically chiefly through participation in the hands-on laboratory sessions, where you will be analysing data with appropriate software. This provides you with the opportunity to receive support on both the theory and technical components of the module simultaneously as well as offering experience of conditions representative of the final assessment.

You can engender further feedback and discussion with the teaching team at any time through our open door policy. In addition, all teaching materials and supplementary material (such as interesting articles) are available through the e-learning portal.

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
(Reading List service online guide for academic staff this containing contact details for the Reading List team – http://library.northumbria.ac.uk/readinglists)

Knowledge & Understanding:
1. Demonstrate knowledge and understanding of parametric estimation procedures and goodness of fit using analytical and numerical techniques
2. Apply modern statistical software to problem solving

Intellectual / Professional skills & abilities:

3. Use appropriate statistical methodology in simple linear regression, residual analysis and experimental design and interpret your findings
4. Select and apply the appropriate statistical process to carry out both parametric and nonparametric hypothesis tests

Personal Values Attributes (Global / Cultural awareness, Ethics, Curiosity) (PVA):

5. Critically evaluate statistical models based on given or sourced data from real-life situations.

You will be formally assessed by a piece of mid-term coursework and a laboratory exam at the end of semester.

SUMMATIVE
1. Coursework (30%) – 1, 2, 4, 5
2. Laboratory examination (70%) – 1, 3, 4

FORMATIVE
Formative assessment will be available on a broadly fortnightly basis in the laboratory sessions via typical lecturer-student interactions, allowing them to extend, consolidate and evaluate their knowledge.

Formative feedback will be provided on your work, and errors in understanding will be addressed reactively using one-to-one or small group discussions. Solutions for laboratory tasks will be provided after you have attempted the questions, allowing you to receive feedback on the correctness of their solutions and to seek help if matters are still not clear.
The module learning outcomes are addressed on the weekly seminar question sheets, which the students attempt during the timetabled laboratory sessions.

None

None

This module showcases the applied nature of statistics and will enhance your hands-on statistical modelling expertise. The central limit theorem is introduced along with several important continuous probability distributions. Estimation of parameters is demonstrated by both maximum likelihood and the method of moments. Hypothesis tests for proportions and non-parametric samples are introduced and the module concludes with the design and analysis of experiments. Modern statistical software will be used throughout the module. Assessment of the module is by one individual assignment (30%) and one formal laboratory examination (70%). The module is designed to provide students with a grounding in an applied statistical environment and experience of statistical software.