Undergraduate Course: Dealing with Statistical Data (SSPS07002)
Course Outline
| School | School of Social and Political Science |
College | College of Humanities and Social Science |
| Credit level (Normal year taken) | SCQF Level 7 (Year 1 Undergraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 0 |
ECTS Credits | 0 |
| Summary | This course is for HSS International Foundation Programme and Open Studies students only. It is not available to undergraduate students. Students enrolled for many social science courses will need to understand ¿ and be ready to question and challenge ¿ the use of statistics in their subject area. A solid grounding in descriptive statistics means that subsequently it is easier for students to understand concepts in inferential statistics. This course will provide an introduction to interpreting and understanding data, data types and methods for summarising and presenting data. It will use software rather than asking students to perform manual calculations, allowing the focus to be on meaning, interpretation and understanding, rather than algebra and mathematics.
This course is designed for students on the HSS International Foundation Programme and for Open Studies students in the Office of Lifelong Learning. A pass in this course will be a requirement for progression to Business Studies, Psychology and Social Work degrees.
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| Course description |
Week 1 Statistics in the media
Week 2 Surveys and identify research question(s)
Week 3 Questionnaire design
Week 4 Introduction to computer analysis system
Week 5 Data analysis and interpretation
Week 6 Data analysis and interpretation
Week 7 An introduction to probability and the concept of statistical significance
Week 8 Class presentations
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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| Academic year 2014/15, Not available to visiting students (SS1)
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Quota: 10 |
| Course Start |
Lifelong Learning - Session 3 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Please contact the School directly for a breakdown of Learning and Teaching Activities |
| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Students will undertake a survey and present their findings. This involves:
1. Group survey design and data collection
2. Group presentation focused on agreed element of the data
3. Framing, asking and responding to individual questions when results are presented.
To pass, students must participate in each of these stages and achieve a minimum of 40%.
|
| Feedback |
Not entered |
| No Exam Information |
|
| Academic year 2014/15, Not available to visiting students (SS1)
|
Quota: 0 |
| Course Start |
Block 5 (Sem 2) and beyond |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
0
(
Seminar/Tutorial Hours 18,
Summative Assessment Hours 10,
Other Study Hours 6,
Directed Learning and Independent Learning Hours
0 )
|
| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
|
| Additional Information (Assessment) |
Students will undertake a survey and present their findings. This involves:
1. Group survey design and data collection
2. Group presentation focused on agreed element of the data
3. Framing, asking and responding to individual questions when results are presented.
To pass, students must participate in each of these stages and achieve a minimum of 40%.
|
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
By the end of this course, students should be able to:
¿ explain about different types of data and the need for appropriate analysis;
¿ discuss issues of sampling fluctuation or error;
¿ use a computer analysis package and interpret computer generated output;
¿ use basic descriptive statistics appropriately;
¿ critically interpret graphs, charts and other summary statistics;
¿ construct a survey instrument for a specific research question; and
¿ question and challenge some statistical claims.
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Reading List
| Students will be given access to web-based materials. |
Additional Information
| Graduate Attributes and Skills |
Exercising informed critical judgement about statistical information.
IT skills, numeracy and data handling, interpersonal and group work skills.
Group presentation skills. |
| Keywords | Not entered |
Contacts
| Course organiser | Mr James Mooney
Tel: (0131 6)50 3077
Email: james.mooney@ed.ac.uk |
Course secretary | Dr Caroline Bamford
Tel: (0131 6)50 4322
Email: Caroline.Bamford@ed.ac.uk |
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