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XX50135: Quantitative methods 2

Follow this link for further information on academic years Academic Year: 2013/4
Follow this link for further information on owning departmentsOwning Department/School: Department of Faculty of Humanities & Social Sciences
Follow this link for further information on credits Credits: 6
Follow this link for further information on unit levels Level: Masters UG & PG (FHEQ level 7)
Follow this link for further information on period slots Period: Semester 2
Follow this link for further information on unit assessment Assessment: CW 100%
Follow this link for further information on supplementary assessment Supplementary Assessment: Like-for-like reassessment (where allowed by programme regulations)
Follow this link for further information on unit rules Requisites: Before taking this unit you must take XX50134
Follow this link for further information on unit content Description: Aims & Learning Objectives:
Aims:
This is an intermediate/advanced course on statistical analysis for postgraduate students following on from Quantitative Methods 1. The aim of the course is to provide students with a critical understanding of the strengths and weaknesses of statistical analysis alongside a detailed knowledge of particular statistical techniques. By the end, the unit will equip students with the skills to contribute to research projects.
Objectives: By the end of the course the students should be able to: Knowledge and understanding:
* Understand the basic principles of statistical analysisIntellectual skills
* Appreciate the strengths and weakness of statistical inquiry
* Interpet the results from chi square tests, t-tests and ANOVAs
* Be able to use, model and interpret correlation, simple linear regression and multiple regression analyses
* Be able to use one or more of a range of advanced statistical techniques including: regression analyses, time series, path analysis, cluster analysis, factor analysis
* Be able to use SPSS to carry out statistical analysis. Professional practice skills:
* Acquire computing skills.

Content:
The course will provide a critical appreciation of statistical analysis as well as covering issues of intermediate and advanced statistical techniques of data analysis. Students will have instruction in both a classroom and a computer lab to build on their prior knowledge of descriptive and inferential statistics. They will use SPSS for windows to apply the techniques they learn in the classroom to analyse data.
Follow this link for further information on programme availabilityProgramme availability:

XX50135 is Compulsory on the following programmes:

School of Management

XX50135 is Optional (DEU) on the following programmes:

Department of Education Department for Health Department of Politics, Languages and International Studies
  • THXX-AFM50 : MRes Politics and International Studies (Full-time)
  • THXX-AFM51 : MRes Politics and International Studies (Full-time)
Department of Psychology
  • THXX-AFM44 : MRes Environment, Energy & Resilience (Full-time)
  • THXX-AFM45 : MRes Environment, Energy & Resilience (Full-time)
Department of Social & Policy Sciences

XX50135 is Optional on the following programmes:

Department of Computer Science
  • RSCM-AFD02 : Doctor of Engineering (EngD) in Digital Media (Full-time)
Department of Education Department of Politics, Languages and International Studies
  • THXX-AFM50 : MRes Politics and International Studies (Full-time)
  • THXX-AFM51 : MRes Politics and International Studies (Full-time)
Department of Psychology Department of Social & Policy Sciences

XX50135 is available for Auditing on the following programmes:

Department of Social & Policy Sciences
Notes:
* This unit catalogue is applicable for the 2013/14 academic year only. Students continuing their studies into 2014/15 and beyond should not assume that this unit will be available in future years in the format displayed here for 2013/14.
* Programmes and units are subject to change at any time, in accordance with normal University procedures.
* Availability of units will be subject to constraints such as staff availability, minimum and maximum group sizes, and timetabling factors as well as a student's ability to meet any pre-requisite rules.