Intermediate inferential statistics: testing and modelling (P01788)

? Credit Points : 20 ? SCQF Level : 11 ? Acronym : SPS-P-P01788

This course will provide an extension beyond the foundation statistics courses to allow students to acquire a deeper and more extensive knowledge and understanding of how to test and model data at various levels of measurement for the purpose of making statistical generalisations.

? Keywords : inference; generalisation; parametric; non-parametric; multiple regression; logistic regression; ordinal resgression; discrete probability distributions; Normal approximation to discrete distributions

Entry Requirements

? Pre-requisites : Pass (minimum 50%) in Core Quantitative Data Analysis 1 and 2 or equivalent

Subject Areas

Home subject area

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

Other subject areas

Law, (School of Law, Schedule F)

Delivery Information

? Normal year taken : Postgraduate

? Delivery Period : Semester 2 (Blocks 3-4)

? Contact Teaching Time : 2 hour(s) per week for 10 weeks

All of the following classes

Type	Day	Start	End	Area
Lecture	Wednesday	09:00	10:50	Central

? Additional Class Information : It is being considered as an e-learning course, so the mandatory field on contact hours is filled in with fictitious numbers currently.

Summary of Intended Learning Outcomes

1. Understand the implications of various types of data measurement and related probability distributions.
2. Understand how to design research to investigate causal and explanatory relationships.
3. Understand the assumptions underpinning various statistical techniques based on asymmetric relationships.
4. Demonstrate ability to solve problems of an inferential nature.
5. Gain proficiency in the use of statistical software to analyse data; e.g. SPSS; Stata.
6. Interpret quantitative solutions in their applied context.

Assessment Information

Take-home exercises at the conclusion of the course. These will require the use of computer software, as appropriate, and test knowledge and understanding across the whole course