HS927-7-SP-CO:
Statistical Analysis
2022/23
Health and Social Care (School of)
Colchester Campus
Spring
Postgraduate: Level 7
Current
Tuesday 17 January 2023
Friday 30 June 2023
15
01 December 2022
Requisites for this module
(none)
(none)
(none)
(none)
(none)
The aim of this module is to introduce students who have no previous experience of quantitative methods to basic and intermediate statistical concepts and procedures. The emphasis is on practical applications, not mathematics although a small amount of elementary mathematics is inevitably required. The module covers the following themes:
* Principles of data analysis, description and inference, and preparation of data for statistical testing
* Conducting uni- and bivariate analysis, tests of association and tests of difference, multivariate analysis and regression modelling
* Interpreting statistical output
Module objectives:
By the end of the module you should be able to:
* Understand the logic of statistical description and inference.
* Know how to interpret basic statistics.
* Conduct elementary and intermediate quantitative data analysis using a statistical software package.
This module will equip students to understand, as well as develop their skills in carrying out a range of statistical tests.
By the end of the module the student will be able to:
Understand the logic of statistical description and inference.
Know how to interpret basic statistics.
Conduct elementary and intermediate quantitative data analysis using a statistical software package.
Students will also get the opportunity to develop the following skills:
Planning and presenting work in an appropriate manner
Writing effectively and presenting information in a clear manner.
Using information technology efficiently to access information and present written work
Using Excel to do basic analysis
Advanced use of SPSS
Enhancing self-directed learning whilst encouraging the purposive use of feedback to reflect on experiences in order to improve learning and development.
Understanding statistical findings is key for anyone wishing to pursue an academic or Professional career. All health and social care policies and treatment recommendations should be based on evidence but in order to understand this evidence base you need to be able to understand the results of any given study and be able to ascertain whether the interpretations made on the basis of those results are appropriate. In addition, those wishing to carry out service evaluations and research within a practice based context will need to be able to demonstrate good statistical ability in addition to being able to use appropriate statistical software.
The aim of this module is to help students develop practical skills in running and interpreting statistical analysis. Students will begin with basic univariate statistics which will serve as a refresher for those already a little familiar with statistics from undergraduate studies. Then they move on to bivariate and finally multivariate analyses. The basic statistics are analysed using Excel but the majority of the module uses SPSS for the purposes of data analysis.
Please note that if insufficient numbers of students (i.e. <10) opt to take this module we may have to cancel it at short notice. If this is the case we will of course notify anyone who has applied to take this course in a particular term as soon as possible and offer an opportunity to discuss alternative options.
All learning and teaching methods are provided online. There are opportunities for indivdiual face to face tutorials with the module lead.
For your study on this module you will be drawing on printed material, a variety of web resources including video clips, and software. You will also engage in online discussion with fellow students. A student copy of SPSS can be obtained from IT services and you will need access to SPSS and Excel throughout the module.
This module does not appear to have a published bibliography for this year.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
| Written Exam |
In class test |
|
100% |
| Written Exam |
Remote Exam via FASER: Stat Analysis (Can't install SPSS? Take exam in IT Lab T) - [EARL23] |
|
|
| Written Exam |
In-class Test Reassessment |
|
|
| Exam |
Main exam: Remote, Open Book, 180 minutes during Early Exams
|
| Exam |
Reassessment Main exam: Remote, Open Book, 180 minutes during September (Reassessment Period)
|
Additional coursework information
80% exam (open book).
20% coursework (in class test)
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Overall assessment
Reassessment
Module supervisor and teaching staff
Prof Andrew Bateman, email: a.bateman@essex.ac.uk.
Andrew Bateman
Andrew Bateman
E: a.bateman@essex.ac.uk
David Bidwell
Student Administrator
E: CPD@essex.ac.uk
No
No
No
Dr Nicola Clarke
Birmingham City University
Senior Lecturer/Professional Navigator/Academic Advisor/Seda Accredited Doctoral
Dr Elaine Lehane
University College Cork
Senior Lecturer
Available via Moodle
Of 10 hours, 4 (40%) hours available to students:
5 hours not recorded due to service coverage or fault;
1 hours not recorded due to opt-out by lecturer(s), module, or event type.
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