Applied Statistical Modelling

Learning Outcomes

Learning Outcomes

Having successfully completed this module you will be able to:

• Design and write a structured report of data analysis in which critical analysis and interpretation of statistical models is demonstrated.
• Understand the assumptions underlying statistical models and implement these checks appropriately.
• Use statistical software to perform statistical analyses and to manipulate quantitative data.
• Demonstrate knowledge and understanding of core methods of descriptive and inferential statistics used in the social sciences and other disciplines.
• Carry out and interpret statistical analyses such as hypothesis tests, linear regression and logistic regression.
• Summarise data with an appropriate statistical model and use these models to describe the relationship between a response and a set of explanatory variables.

This module gives a broad introduction to quantitative methods of analysis. Indicative content includes:

• descriptive statistics and presentation of data using tables and graphs
• the Normal distribution, sampling distributions and the central limit theorem,
• confidence intervals and hypothesis tests for means and proportions
• chi-squared test of independence, two sample t-tests, and correlation
• simple and multiple linear regression with different types of categorical covariates and interactions
• logistic regression,
• multinomial logistic regression
• ordinal logistic regression.

Teaching and learning methods

Material will be delivered through lectures and computer workshops. There is likely to be a pre-module session during the introductory week to ensure that all participants are at the same level before the module formally begins. Teaching will be delivered through lectures, workshop activities, and in-class exercises. A range of resources will also be provided for further self-directed study.

Resources & Reading list

Textbooks

Field, A.. Discovering Statistics Using SPSS. London: Sage.

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

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

Foster, L., Diamond, I. and Jefferies, J. (2015). Beginning Statistics: an Introduction for Social Scientists. London: Sage.

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

Summative

This is how we’ll formally assess what you have learned in this module.

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.

Repeat

An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.

Repeat Information

Repeat type: Internal & External