Undergraduate Course: Doing Social Research with Statistics (SSPS08007)
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 2 Undergraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | This course is designed to provide intermediate level statistical data analysis skills to students in the 'with Quantitative Methods' degree programs in SPS. This course will have a practical and applied focus. |
| Course description |
This course covers regression models for binary, ordinal, nominal and count outcome variables. This will include binomial logistic regression, ordinal logistic regression, multinomial logistic regression and poisson regression.
This course will use the statistical data analysis package, Stata. This course will introduce skills in data management and data analysis using Stata.
The course is delivered via lectures and interactive computer lab sessions.
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Course Delivery Information
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| Academic year 2022/23, Not available to visiting students (SS1)
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Quota: None |
| Course Start |
Semester 2 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 11,
Seminar/Tutorial Hours 22,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
163 )
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
1) 75% A short research report on a substantive topic containing the application of one of the regression analysis techniques covered in this course. The report should be no more than 2000 words long which includes a substantive introduction, descriptive statistics, a regression model, and a set of substantive conclusions.
2) 25% An annotated Stata .do file which contains all the code required to reproduce the analysis presented in the report. There is no word limit for the .do file, but parsimony is encouraged. |
| Feedback |
Students will receive feedback on an analysis project to be submitted in late March. |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Use the statistical data analysis package Stata to effectively and efficiently analyse social science data resources.
- Appreciate the core differences between linear regression models and logistic regression models.
- Appropriately undertake analyses using regression models for categorical dependent variables (e.g. binary logistic regression, multinomial logistic regression, ordered logistic regression, and poisson regression).
- Accurately interpret analyses of categorical dependent variables.
- Effectively report analyses of categorical dependent variables.
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Reading List
Indicative Readings
Acock, A.C., 2016. A gentle introduction to Stata., College Station, Texas: Stata Press.
Kohler, U. and Kreuter, F., 2009. Data Analysis Using Stata. College Station Texas: Stata Press.
Long, J.S. 2009. The Workflow of Data Analysis Using Stata. College Station Texas: Stata Press.
Long, J.S. & Freese, J., 2014. Regression models for categorical dependent variables using Stata., College Station, Texas: Stata Press.
Mehmetoglu, M. and Jakobsen, T.G., 2016. Applied statistics using Stata: a guide for the social sciences. London: Sage.
Treiman, D. J., 2009. Quantitative Data Analysis: Doing Social Research to Test Ideas. San Francisco: Jossey-Bass.
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Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | Dr Roxanne Connelly
Tel:
Email: |
Course secretary | Mr Ethan Alexander
Tel: (0131 6)50 4001
Email: |
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