|Semester 1 Credit Value:||10|
1.To introduce students to the principles of data analysis and experimental design and provide them with an introduction to statistics.
2. To show students how to describe and analyse data systematically.
3. To demonstrate to students how to formulate hypotheses and use data to evaluate those hypotheses.
Basic experimental design, hypothesis testing, descriptive statistics, distributions, elementary statistics, chi squared, Fisher exact, Wilcoxon, Wilcoxon-Mann Whitney, t tests, tests of association, nonparametric analyses, Introduction to statistical packages. Deciding how to choose a test.
|Guided Independent Study||Assessment preparation and completion||1||20:00||20:00||N/A|
|Scheduled Learning And Teaching Activities||Lecture||10||1:00||10:00||N/A|
|Scheduled Learning And Teaching Activities||Practical||14||1:00||14:00||N/A|
|Guided Independent Study||Independent study||1||56:00||56:00||N/A|
Lectures introduce the concepts and methods
Statistical analysis is practiced over a series of computer-based practical classes using an Excel workbook for basic statistical analysis.
The format of resits will be determined by the Board of Examiners
|Written Examination||120||1||A||100||Class test.|
Tests directly the skills taught in the course, requiring students to choose, implement and interpret appropriate statistical tests for data analysis.
Disclaimer: The University will use all reasonable endeavours to deliver modules in accordance with the descriptions set out in this catalogue. Every effort has been made to ensure the accuracy of the information, however, the University reserves the right to introduce changes to the information given including the addition, withdrawal or restructuring of modules if it considers such action to be necessary.