Core quantitative data analysis for social research: part 2 (P01509)

? Credit Points : 10 ? SCQF Level : 11 ? Acronym : SPS-P-P01509

This web-based course aims to give postgraduate students an understanding of core statistical concepts and methods for social research. The course is designed for students who have a basic grasp of descriptive and exploratory statistics (e.g. as in CQDASR- part 1) and a working knowledge of SPSS. In particular, and in line with ESRC postgraduate research training guidelines, the course aims to ensure that all students completing the course are able to demonstrate proficiency in certain key methods. Students will also achieve a level of competence that enables them to use, model and interpret inferential and simple multivariate statistical analysis.
The course will explore principles of inference, measures of association and elementary multivariable analysis. Course content will include: elementary probability distributions; estimation and population variance; hypothesis testing and significance tests; tabular data; measures of association between variables at different levels of measurement; modelling through contingency tables and multiple regression.

Entry Requirements

none

Subject Areas

Home subject area

Postgraduate (School of Social and Political Studies), (School of Social and Political Studies, Schedule J)

Delivery Information

? Normal year taken : Postgraduate

? Delivery Period : To be arranged/Unknown

? Contact Teaching Time : 1 hour(s) per week for 10 weeks

Summary of Intended Learning Outcomes

By the end of the course students will:
o Be able to understand and apply a range of quantitative methods and tools
o Understand statistical modelling and be capable of using SPSS for Windows to perform statistical analysis.
o Have experience of working with large data sets at different levels of aggregation
o Understand how to access information about data sources
o Have experience of utilising web-based resources for learning
o Be able to efficiently access IT resources
o Be able to use computer software for statistical analysis of several variables