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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

Field, A.. Discovering Statistics Using SPSS. 

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

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

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

Assessment

Summative

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

Referral

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

Repeat Information

Repeat type: Internal & External

Costs

Costs associated with this module

Students are responsible for meeting the cost of essential textbooks, and of producing such essays, assignments, laboratory reports and dissertations as are required to fulfil the academic requirements for each programme of study.

In addition to this, students registered for this module typically also have to pay for:

Books and Stationery equipment

Recommended texts for this module may be available in limited supply in the University Library and students may wish to purchase reading texts as appropriate.

Please also ensure you read the section on additional costs in the University’s Fees, Charges and Expenses Regulations in the University Calendar available at www.calendar.soton.ac.uk.

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