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Session: 2022/23
Last modified: 10/01/2023 11:07:56
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Title of Module: Probability and Statistics |
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Code: MATH08010 |
SCQF Level: 8
(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 extends the ideas in basic statistics and probability from Dealing with Data (MATH07001) to a study of more advanced probability concepts. Having consolidated an understanding the concept of probability, the emphasis will be on extending that understanding in a study of discrete and continuous random variables and probability distributions.
A range of commonly occurring discrete probability distributions will be discussed including binomial, Poisson, geometric and hypergeometric distributions. Additionally, a range of commonly occurring continuous probability distributions will be discussed including uniform, exponential, and normal distributions. The importance of the normal distribution will be discussed in detail, including reference to such topics as the central limit theorem.
The ideas of measuring average and variability in MATH07001 will be extended to the concepts of expectation and variance of a random variable. Moments of a random variable will be discussed.
The ideas of sampling distributions, confidence limits and intervals will be introduced.
Suitable statistical software package(s) will be used for visual understanding of the concepts, calculations and predictions.
The Graduate Attributes relevant to this module are given below:
- Academic: Critical thinker; Analytical; Inquiring; Knowledgeable; Problem-solver; Digitally literate; Autonomous.
- Personal: Effective communicator; Motivated, Creative; 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.
Implement suitable analytic procedures in problems involving discrete random variables and probability distributions.
L2.
Implement suitable analytic procedures in problems involving continuous random variables and probability distributions.
L3.
Demonstrate an understanding of sampling distributions, and use standard analytic techniques to estimate confidence limits/intervals.
L4.
Use suitable software to perform statistical analysis and interpret its output. |
| 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 8.
Demonstrating a knowledge and understanding of the concept of a probability distribution and resulting calculations.
Demonstrating basic awareness of the application of statistical techniques, as appropriate, to the solution of problems.
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| Practice: Applied Knowledge and Understanding |
SCQF Level 8.
Using a range of standard techniques of calculation in solving standard problems in statistics and probability, and making valid interpretations of these. |
| Generic Cognitive skills |
SCQF Level 8.
Using a range of methods to analyse well-defined problems in relevant mathematical or statistical contexts. |
| Communication, ICT and Numeracy Skills |
SCQF Level 8.
Using suitable software to obtain and present results to statistical problems, as appropriate. |
| Autonomy, Accountability and Working with others |
SCQF Level 8.
Working autonomously and with others to solve and produce short reports on statistical problems.
Conceptualising and analysing problems informed by professional and research issues.
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| Pre-requisites: |
Before undertaking this module the student should have
undertaken the following:
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Module Code:
MATH07001
| Module Title:
Dealing with Data
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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 | 146 |
| Personal Development Plan | 6 |
| 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:
Statistical software, e.g. Excel, SPSS, R.
Generic software, e.g. Microsoft Word.
“Probability and Statistics” class notes as published on the University VLE.
"Introduction to Probability, Statistics and Random Processes", H Pishro-Nik
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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 | Alan Walker |
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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 50% of the final mark. This will involve appropriate statistical analyses and uses suitable software. |
| Closed book examination worth 50% of the final mark. |
(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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