Undergraduate Course: Doing Social Research with Statistics (SSPS08007)
|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
|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.
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.
Course Delivery Information
|Academic year 2020/21, Not available to visiting students (SS1)
|Learning and Teaching activities (Further Info)
Lecture Hours 22,
Seminar/Tutorial Hours 22,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|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.
||Students will receive feedback on an analysis project to be submitted in late March.
|No Exam Information
On completion of this course, the student will be able to:
- Make effective use of regression models for categorical dependent variables, including binomial logistic regression, multinomial logistic regression, and ordinal logistic regression.
- Use the statistical data analysis package Stata to estimate logistic regression models.
- Effectively interpret estimates from logistic regression models using different approaches.
- ake effective use of regression models for count data (e.g. the Poisson model).
- Use the statistical data analysis package Stata to estimate regression models for count data, and effectively interpret these models.
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.
|Graduate Attributes and Skills
|Course organiser||Dr Roxanne Connelly
|Course secretary||Mr Daniel Jackson
Tel: (0131 6)50 8253