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Session: 2022/23
Last modified: 10/01/2023 11:16:06
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Title of Module: Regression Methods and Experimental Design |
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Code: MATH10008 |
SCQF Level: 10
(Scottish Credit and Qualifications Framework) |
Credit Points: 20 |
ECTS: 10
(European Credit Transfer Scheme) |
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| School: | School of Computing, Engineering and Physical Sciences |
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| Module Co-ordinator: | Laura
Stewart |
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| Summary of Module |
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This module aims to prepare the participant to design and conduct research and statistically analyse research output. The emphasis of the module will be the understanding of the concepts of research hypotheses and their application on research design and research output analysis.
Concepts from linear single regression modelling are reviewed and extended to include topics such as one- and two-way ANOVA. Experimental design methods and topics are discussed for categorical data in order to perform independence testing and group comparison. Multivariate and logistic linear regression analysis is also introduced.
Participants are given the opportunity to demonstrate their knowledge of these concepts by creating research questions and design studies and applying suitable analytical procedures on the research output.
Suitable statistical package(s) are used to demonstrate understanding of the experimental design and modelling concepts.
The Graduate Attributes relevant to this module are given below:
- Academic: Critical thinker; Analytical; Inquiring; Knowledgeable; Problem-solver; Digitally literate; Autonomous .
- Personal: Effective communicator; Resilient
- Professional: Collaborative; Research-minded; Socially responsible; Ambitious; Driven.
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| Module Delivery Method |
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| Face-To-Face | Blended | Fully Online | HybridC | HybridO | Work-based Learning |
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Face-To-Face
Term used to describe the traditional classroom environment where the students and the lecturer meet synchronously in the same room for the whole provision.
Blended
A mode of delivery of a module or a programme that involves online and face-to-face delivery of learning, teaching and assessment activities, student support and feedback. A programme may be considered “blended” if it includes a combination of face-to-face, online and blended modules. If an online programme has any compulsory face-to-face and campus elements it must be described as blended with clearly articulated delivery information to manage student expectations
Fully Online
Instruction that is solely delivered by web-based or internet-based technologies. This term is used to describe the previously used terms distance learning and e learning.
HybridC
Online with mandatory face-to-face learning on Campus
HybridO
Online with optional face-to-face learning on Campus
Work-based Learning
Learning activities where the main location for the learning experience is in the workplace.
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| Term(s) for Module Delivery |
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(Provided viable student numbers permit).
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| Term 1 | | Term 2 | | Term 3 | |
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| Learning Outcomes: (maximum of 5 statements) |
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On successful completion of this module the student will be able to:
L1.
Formulate suitable research hypotheses for a statistical test.
L2.
Create a suitable experimental design and build a suitable corresponding model.
L3.
Analyse and interpret output from the test.
L4.
Use suitable computer software to perform and present appropriate analyses. |
| Employability Skills and Personal Development Planning (PDP) Skills |
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| SCQF Headings |
During completion of this module, there will be an opportunity to achieve
core skills in:
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| Knowledge and Understanding (K and U) |
SCQF Level 10.
Demonstrating a knowledge and understanding of concept of experimental design and linear regression modelling.
Demonstrating awareness of the application of statistical hypothesis, as appropriate, to the solution of problems.
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| Practice: Applied Knowledge and Understanding |
SCQF Level 10.
Using a range of standard techniques of decision making and statistical model building as well as the application of the hypothesis in research to solve standard statistical problems, as appropriate, and making valid interpretations of these. |
| Generic Cognitive skills |
SCQF Level 10.
Using a range of methods to analyse well-defined problems in relevant statistical contexts. |
| Communication, ICT and Numeracy Skills |
SCQF Level 10.
Conceptualising and analysing problems informed by professional and research issues.
Using suitable software to obtain, present and make valid interpretation of statistical problems and results, as appropriate.
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| Autonomy, Accountability and Working with others |
SCQF Level 10.
Working autonomously to produce short reports on statistical problems.
Collaborating with others in a small team to solve statistical problems.
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| Pre-requisites: |
Before undertaking this module the student should have
undertaken the following:
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Module Code:
MATH09012
| Module Title:
Statistical Estimation and Inference
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| Other: | or equivalent |
| Co-requisites | Module Code:
| Module Title:
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* Indicates that module descriptor is not published.
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| Learning and Teaching |
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Learning Activities
During completion of this module, the learning activities undertaken to
achieve the module learning outcomes are stated below:
| Student Learning Hours
(Normally totalling 200 hours):
(Note: Learning hours include both contact hours and hours spent on other learning activities) |
| Lecture/Core Content Delivery | 24 |
| Tutorial/Synchronous Support Activity | 12 |
| Laboratory/Practical Demonstration/Workshop | 12 |
| Independent Study | 152 |
| 200
Hours Total
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**Indicative Resources: (eg. Core text, journals, internet
access)
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The following materials form essential underpinning for the module content
and ultimately for the learning outcomes:
“Regression Methods and Experimental Design” class notes on the University VLE.
Suitable software, e.g. Excel, SPSS, R and Word.
"Regression Modeling Strategies", FE Harrell jr.
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(**N.B. Although reading lists should include current publications,
students are advised (particularly for material marked with an asterisk*) to
wait until the start of session for confirmation of the most up-to-date
material)
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| Engagement Requirements |
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In line with the Academic Engagement Procedure, Students are defined as academically engaged if they are regularly engaged with timetabled teaching sessions, course-related learning resources including those in the Library and on the relevant learning platform, and complete assessments and submit these on time. Please refer to the Academic Engagement Procedure at the following link: Academic engagement procedure |
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Supplemental Information
| Programme Board | Physical Sciences |
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| Assessment Results (Pass/Fail) |
No
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| Subject Panel | Physical Sciences |
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| Moderator | Kwok Chi Chim |
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| External Examiner | P Wilson |
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| Accreditation Details | |
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| Version Number | 1.05 |
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| Assessment: (also refer to Assessment Outcomes Grids below) |
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| Coursework worth 100% of the final mark. This will involve appropriate statistical analyses and use suitable software, together with a final presentation. |
(N.B. (i) Assessment Outcomes Grids for the module
(one for each component) can be found below which clearly demonstrate how the learning outcomes of the module
will be assessed.
(ii) An indicative schedule listing approximate times
within the academic calendar when assessment is likely to feature will be
provided within the Student Handbook.)
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Assessment Outcome Grids (Footnote A.)
Footnotes
A. Referred to within Assessment Section above
B. Identified in the Learning Outcome Section above
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Note(s):
- More than one assessment method can be used to assess individual learning outcomes.
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Schools are responsible for determining student contact hours. Please refer to University Policy on contact hours (extract contained within section 10 of the Module Descriptor guidance note).
This will normally be variable across Schools, dependent on Programmes &/or Professional requirements.
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| Equality and Diversity |
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The module is suitable for any student satisfying the pre-requisites.
UWS Equality and Diversity Policy |
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(N.B. Every effort
will be made by the University to accommodate any equality and diversity issues
brought to the attention of the School)
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