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The University of Southampton
Courses

STAT6117 Applied Statistical Modelling

Module Overview

This is a postgraduate advanced module in applied statistical modelling designed to equip students with highly sought after employability skills in data analysis. The module will cover a wide range of statistical models including a revision of introductory statistics, linear regression, logistic regression, multinomial logistic regression, log-linear models, models for rates (Poisson regression), and ordinal logistic regression. Some theory behind the methods will be covered, although the emphasis is on the practical application of these methods using statistical software. In this respect, students will be introduced to the statistical software of their choice Stata, SPSS or R.

Aims and Objectives

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

  • Summarise data with an appropriate statistical model
  • Report writing
  • Use these models to describe the relationship between a response and a set of explanatory variables
  • Carry out and interpret statistical analyses such as hypothesis tests, linear regression and logistic regression
  • Check the model and interpret the results
  • Use of statistical software (SPSS/R/Stata) effectively
  • Gain an understanding of some of the basic theory behind statistical modelling.
  • Problem analysis and problem solving
  • Statistical computing
  • Data handling and manipulation

Syllabus

Normal distribution, sampling distributions and the central limit theorem, confidence intervals, hypothesis tests for means and proportions, chi-squared test of independence, two sample t-tests, correlation, simple linear regression, multiple linear regression, model selection and diagnostics, logistic regression, multinomial logistic regression, log-linear models, models for rates (Poisson regression), ordinal logistic regression.

Learning and Teaching

Teaching and learning methods

Teaching will be through a combination of lectures, tutorials and computer workshops. Learning activities will include learning in lectures, which will cover explanations of the statistical modelling techniques and their use, discussing problems during the tutorials, as well as by independent study. The computer workshops will provide hands-on experience of the analysis of data and the application of the techniques introduced in the lectures, enabling you to undertake the statistical computing element of the coursework assignment.

TypeHours
Teaching40
Independent Study160
Total study time200

Resources & Reading list

Fox, J. (2016). Applied Regression Analysis and Generalised Linear Models. 

Agresti, A. (2013). Categorical Data Analysis. 

Mehmetoglu, M. and Jakobsen, G. (2017). Applied Statistics using Stata. A Guide for the Social Sciences.. 

Field, A.. Discovering Statistics Using SPSS. 

Assessment

Summative

MethodPercentage contribution
Coursework  (3500 words) 60%
Coursework  (3000 words) 40%

Referral

MethodPercentage contribution
Coursework  (3500 words) 60%
Coursework  (3000 words) 40%

Repeat Information

Repeat type: Internal & External

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