# Module ICE-0101:Essential Mathematics

### Module Facts

Run by School of Computer Science and Electronic Engineering

20 Credits or 10 ECTS Credits

Semester 1

Organiser: Dr David Edward Perkins

### Overall aims and purpose

This module will provide you with the mathematical skills and knowledge needed for degree-level study. The module will focus on essential mathematical and statistical skills and techniques and will prepare you to utilize these in a subject-specific context during your degree studies.

### Course content

Topics areas covered in this module may include: Algebra and Functions: understand and use the laws of indices. Solution of linear and quadratic equations and manipulation of formulae. Solution of simultaneous equations. The use of fractions.

Statistical Sampling: the importance of sample populations in the statistical analysis of data understand and the use sampling techniques, including simple random, systematic and opportunity sampling. Selection and critique of sampling techniques in the context of a statistical problem.

Data presentation and Interpretation: Histograms and their relationship to statistical distributions. Scatter diagrams and correlation. Measures of central tendency and variation, including standard deviation. Dealing with outliers in datasets.

Probability: understanding independent and mutually exclusive events. Conditional probability. Venn diagrams. Tree diagrams. Calculating probabilities.

Statistical Distributions: understand and use probability distributions, including the normal distribution and binomial distribution. Use of different distributions to model real world situations and evaluate their appropriateness.

Statistical hypothesis testing: understand and apply the language of hypothesis testing. Conduct statistical hypothesis tests, including in relation to the normal or binomial distribution.

### Assessment Criteria

#### excellent

Grade A- and above An excellent understanding of mathematical and statistical techniques with virtually no errors. Is able to formulate appropriate solutions to accurately solve tasks and questions with virtually no inaccuracies and misconceptions evident. Outputs can be understood, which demonstrate excellent structure and/or coherence.

#### threshold

Grade D- to D+ Basic understanding of mathematical and statistical techniques but some errors present. Is able to formulate appropriate solutions to accurately solve tasks and questions but with some inaccuracies and misconceptions evident. Outputs can be understood, but lack structure and/or coherence.

#### C- to C+

Grade C- to C+ A clearer understanding of mathematical and statistical techniques. Is able to formulate appropriate solutions to accurately solve tasks and questions but with some minor inaccuracies and misconceptions evident. Outputs can be understood, with possible improvements to structure and/or coherence.

#### good

Grade B- to B+ A good understanding of mathematical and statistical techniques with few errors. Is able to formulate appropriate solutions to accurately solve tasks and questions with only very minor inaccuracies and misconceptions evident. Outputs can be understood, which demonstrate good structure and/or coherence.

### Learning outcomes

1. Correctly solve mathematical problems.

2. Correctly utilize statistical techniques to analyse data.

3. Understand risk, probability and variation in statistics

4. Understand and evaluate assumptions made when modelling or solving problems

### Assessment Methods

Type Name Description Weight
CLASS TEST Test 1: algebra and functions

Multiple choice questions

20
CLASS TEST Test 2: sampling, data presentation and probability

Multiple choice questions

20
EXAM Exam

Multiple choice and short answer questions

40
CLASS TEST Test 3: distributions and hypothesis testing

Multiple choice questions

20

### Teaching and Learning Strategy

Hours
Lecture

24*2 hour lectures

48
Tutorial

12*1 hour tutorials

12
Private study

Time spent working on guided and independent study and on the preparation of assignments.

140

### Transferable skills

• Numeracy - Proficiency in using numbers at appropriate levels of accuracy
• Computer Literacy - Proficiency in using a varied range of computer software
• Self-Management - Able to work unsupervised in an efficient, punctual and structured manner. To examine the outcomes of tasks and events, and judge levels of quality and importance
• Information retrieval - Able to access different and multiple sources of information
• Inter-personal - Able to question, actively listen, examine given answers and interact sensitevely with others
• Critical analysis & Problem Solving - Able to deconstruct and analyse problems or complex situations. To find solutions to problems through analyses and exploration of all possibilities using appropriate methods, rescources and creativity.

### Subject specific skills

• Solve problems logically and systematically;
• Analyse and display data using appropriate methods and mathematical techniques;

### Resources

#### Resource implications for students

Students will be required to access online resources. Use of personal computers or University facilities will enable this.