Module Information
Course Delivery
| Delivery Type | Delivery length / details |
|---|---|
| Lecture | 22 hours |
| Practical | up to 6 hours of workshops |
Assessment
| Assessment Type | Assessment length / details | Proportion |
|---|---|---|
| Semester Assessment | Written problem based assignment on techniques introduced in the module. | 20% |
| Semester Exam | 1.5 Hours Written Exam | 80% |
| Supplementary Assessment | Resubmission of failed/non-submitted coursework components of ones of equivalent value. | 20% |
| Supplementary Exam | 1.5 Hours Written Exam | 80% |
Learning Outcomes
On successful completion of this module students should be able to:
1. In the area of Number Representation perform tasks such as:
Carry out calculations in 2's complement and excess-n representations; Calculate precision and accuracy of floating point representations; Give examples of unexpected results of comparison that occur with floating point representations, and suggest programming alternatives.
2. In the area of Geometry perform tasks such as:
Relate concepts from 2 and 3-dimensional coordinate geometry to vector algebra; perform computations using vectors and matrices to implement elementary algorithms used in computer graphics and robotics
3. In the area of Counting Techniques perform tasks such as:
Use sum and product rules, inclusion exclusion and the pigeonhole principle to answer questions about data and communications resources.
4. In the area of Probability and Statistics perform tasks such as:
Describe the concept of variability and its manifestation in statistical diagrams; Describe the concepts involved in the statistical modelling of randomness.
5. In the area of Induction carry out proof by induction and complete induction over N.
6. In the area of Calculus perform tasks such as:
Calculate the gradient of a curve and locate maxima, minima and turning points of a function; Calculate indefinite and definite integrals and find the area under a curve.
Aims
Brief description
This module provides a range of skills needed for successful study in graphics, communications, algorithm analysis, vision, robotics and artificial intelligence.
Content
1.Number representation: (4 lectures)
Calculations in 2's complement and excess-n representations ; precision and accuracy of floating point representations; examples of zero-divisions and unexpected results of comparison that occur because a floating point representation comprises a finite set of representatives of real intervals; programming alternatives; cancellation and guard digits.
2.Geometry: (6 lectures)
2 and 3-dimensional coordinate geometry; basic trigonometrical functions and identities, relating angles in different quadrants; vector and matrix algebra; elementary algorithms in computer graphics and robotics.
3.Counting Techniques: (2 lectures)
Sum and product rules, inclusion exclusion and the pigeonhole principle; application of counting techniques to problems in data structures and communications.
4.Probability and Statistics: (4 lectures)
Summarising data. Shapes of distributions. Binomial experiments and large sample behaviour. The Poisson distribution as a model for randomness. Quick and graphical tests for the Poisson distribution. Waiting times and the exponential distribution. Basic ideas of significance and goodness of fit.
5.Induction: (3 lectures)
What is induction? Proof by induction over N; the Principle of Complete Induction.
6.Calculus: (3 lectures)
Gradient of a curve; maxima, minima and turning points of a function; indefinite and definite integrals; area under a curve.
Module Skills
| Skills Type | Skills details |
|---|---|
| Application of Number | Inherent to subject. |
| Communication | In assignment and exam. |
| Improving own Learning and Performance | |
| Information Technology | |
| Personal Development and Career planning | |
| Problem solving | Inherent to subject. |
| Research skills | |
| Subject Specific Skills | |
| Team work |
Notes
This module is at CQFW Level 4