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| Module Availability |
2nd Semester |
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| Assessment Pattern |
Two exercises
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| Module Overview |
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| Prerequisites/Co-requisites |
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| Module Aims |
To give students experience of analysing data sets from recent surveys such as the General Household Survey, using personal computers in the departmental laboratory.
Emphasis throughout the course is on intuitive understanding rather than on rigorous derivation. |
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| Learning Outcomes |
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| Module Content |
Data Analysis:
Frequency counts and simple data description
Crosstabulation of two variables
Measuring association between variables
Crosstabulation and causal modelling
Introduction to regression analysis
Statistical inference :
Sampling
Estimation
Hypothesis testing
Statistical modelling
Multiple regression
The examination of residuals
Dummy variable regression
Structural equation models
Factor analysis
Attitude scale construction
Dummy variables and analysis of variance
Loglinear modelling
Model fitting and selection
Logit regression |
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| Methods of Teaching/Learning |
| In addition to the formal lectures (which often become informal) there are practical classes at which students acquire skills with appropriate computer software and are able to seek clarification of concepts and methods. The focus of the second half of the course is on building statistical models. |
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| Selected Texts/Journals |
Hosmer, D.W. and Lemeshow, S (2000) Applied Logistic Regression (2nd edition) John Wiley & Sons
Tabachnick, B.G. and Fidell, L.S. (2006), Using Multivariate Statistics, Prentice Hall
Tarling, R. (2008) Statistical Modelling for Social Researchers. Routledge. |
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| Last Updated |
| 27th August 2009 |
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