AM0S05 - Application of Mathematical Skills 01 Aug 2023 - 31 Aug 2029 | Version 3
Associated Module Information
| Module Code: | AM0S05 | ||
|---|---|---|---|
| Module Title: | Application of Mathematical Skills | ||
| Faculty: | Faculty of Computing, Engineering and Science | ||
| Faculty Group: | Computing and Mathematical Sciences | ||
| Faculty Sub Group: | Mathematical Sciences | ||
| Module Leader: | Graeme Boswell | ||
| Module Team: | Hannah Seale, Shane Galvin, Graeme Boswell | ||
| First Intended Intake: | SEP 2018 | Final Year of Intake: | 2028 |
| Date Closed: | |||
| Credit Value: | 20 | Credit Level: | 3 |
| Language: | English | ||
| Percentage of Module Taught in Welsh: | 0 | ||
| Equivalent Module: | |||
| HECOS codes: | 100403 - mathematics | ||
| HECOS Code Weighting: | 100 | ||
Document Version Information
| Version | 3 |
|---|---|
| Valid From | 01 Aug 2023 |
| Valid To | 31 Aug 2029 |
Module Aims
To provide students with confidence in applying basic calculus and statistical methods.
To provide students with examples of applications in statistics and calculus relevant to their subject area.
Content Summary
Introduction to Statistics. Types of data. Population and samples. Frequency tables. Graphical representation of data.
Cumulative frequency, grouped data and histograms.
Sigma notations. Measures of location: maximum, minimum, range, mean, median, mode. Quartiles, Interquartile range.
Measures of variation: deviations, variance and standard deviation.
Measures of correlation: covariance and correlation coefficient. Introduction to linear regression.
Introduction to the use of Microsoft Excel to analyse data.
Introduction to probability.
Basic Differentiation - differentiation of powers of x and polynomials, differentiation of exponential, logarithmic and trigonometric functions
Basic integration - integration as the reverse of differentiation, integration of polynomial, exponential, logarithmic and trigonometric functions.
Applications of the above content relevant to the students subject area.
Learning and Teaching Methods
| Activity Type | Hours |
|---|---|
| Lecture | 24 |
| Practical classes and workshops | 24 |
| Independent Study | 72 |
| Directed Study | 80 |
| Total Hours Selected | 200 |
Learning Outcomes
| # | Learning Outcome |
|---|---|
| LO1 | Apply a range of basic calculus and statistical techniques, and interpret the solutions appropriately. |
| LO2 | To understand the basic calculus and statistics behind relevant applications and to be able to identify and perform relevant mathematical and statistical techniques appropriately. |
Module Requisites
N/A
Assessment Criteria
| Assessment Category | Assessment Type | Description | Duration | Word Count | Weight (%) | Best of? | Pass Mark |
|---|---|---|---|---|---|---|---|
| Asynchronous Assessment | Practical Coursework 1 (Asynch) | An excel based data analysis task. | 0 | 1000 | 40 | No | 40 |
| Synchronous Onsite Assessment | Classroom Test - Time Constrained (Onsite) 1 | Open book test with a course formula sheet that can be annotated as seen fit. | 60 | N/A | 60 | No | 40 |
Assessment Matrix
| Assessment Type | Learning Outcomes | ||
|---|---|---|---|
| LO1 | LO2 | ||
| Practical Coursework 1 (Asynch) | ✔ | ✔ | |
| Classroom Test - Time Constrained (Onsite) 1 | ✔ | ✔ | |