Undergraduate Course: Introduction to Statistics for Social Science (SSPS08008)
Course Outline
| School | School of Social and Political Science |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 8 (Year 1 Undergraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course introduces fundamental statistical concepts for social science data analysis for students undertaking 'with Quantitative Methods' degrees. |
| Course description |
The course is an introduction to statistically orientated data analysis for social science research. It is designed for students who also study Sociology, Social Policy, Politics, and International Relations. The course will introduce a broad range of key statistical concepts and tools for social science research. These include quantitative data and questions; the variable by case matrix; distributions; measures of central tendency and dispersion; research designs and sampling; statistical inference; bivariate associations; and introduction to linear regression. The course will also introduce students to the statistical data analysis workflow, and students will be encouraged to develop a rudimentary understanding of transparent and reproducible statistically orientated social science data analysis. Students will be introduced to the general purpose statistical software package Stata.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
Students MUST have passed:
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Co-requisites | |
| Prohibited Combinations | |
Other requirements | While entry to this course normally requires a pass at B in Mathematics at SQA Higher or A-level, students with confidence in their level (high school equivalent) of mathematical knowledge will be considered for admission. Please contact the course convenor if would like to join the course but have any concerns about your current Mathematical knowledge being sufficient. |
Course Delivery Information
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| Academic year 2024/25, Not available to visiting students (SS1)
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Quota: 60 |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 10,
Seminar/Tutorial Hours 20,
Formative Assessment Hours 1,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
165 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
40% Exercise Assessment
60% Data Analysis Practical Assessment |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Understand a broad range of key statistical concepts for social science research
- Present and communicate results from statistical analysis
- Demonstrate that they have developed foundational skills and expertise in statistically orientated social science data analysis
- Use statistical data analysis software to solve research problems
- Have an understanding of the statistical data analysis workflow
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Reading List
Diez, D.; Cetinkaya-Rundel, M., & Barr, C.D. (2022). OpenIntro Statistics, Fourth Edition. Available at https://www.openintro.org/go/?id=os4_for_screen_readers&referrer=/book/os/index.php
Huntington-Klein, N. (2021). The effect: An introduction to research design and causality. CRC Press. Online version available at https://theeffectbook.net/
Additional readings
De Vries, R. (2019). Critical Statistics: Seeing beyond the headlines. Macmillan International.
Bueno de Mesquita, E., & Fowler, A. (2021). Thinking clearly with data: A guide to quantitative reasoning and analysis. Princeton University Press
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Statistics,Data Analysis,Stata |
Contacts
| Course organiser | Dr Ginevra Floridi
Tel: (01316) 517112
Email: Ginevra.Floridi@ed.ac.uk |
Course secretary | Mr Ian McClory
Tel: (0131 6)50 3932
Email: Ian.McClory@ed.ac.uk |
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