Core quantitative data analysis for social research: part 1 (P01508)

? Credit Points : 10 ? SCQF Level : 11 ? Acronym : SPS-P-P01508

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 little or no previous experience or knowledge of statistics, or for those who feel they need a refresher course on the subject. In particular, and in line with ESRC postgraduate training guidelines, the course aims to ensure that all students completing the course are able to demonstrate proficiency in certain key methods, and in the use, interpretation and presentation of techniques for the analysis of quantitative data.
The course will explore descriptive and exploratory data analysis and data management and analysis using statistical software (SPSS). Course content will include: the structure of social science data - cases, variables, values, data sets and missing data; levels of measurement; frequency distributions; graphical representation of data; measures of central tendency, dispersion and shape; normal distribution, standard scores and regrouping of variables.

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 Understand the significance of links between theory and method and understand the epistemological implications of particular methodological approaches
o Be able to understand and apply a range of quantitative methods and tools
o Know how to interpret basic statistics
o Have a thorough grounding in descriptive and exploratory data analysis techniques
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 Have an understanding of how to use computer software for descriptive and exploratory statistical analysis