ARHIV DRUŽBOSLOVNIH PODATKOV

The course will focus on the use of statistical modelling to study association between variables, with focus on simple and multiple linear regression, where the dependent variable is a continuous variable. This course is designed to follow Survey Data Analysis I. (The course does not cover logistic or multinomial regression, where the dependent variable is binary or categorical. This is covered in the CASS course 'Regression Methods').

Course Objectives:
To develop a practical understanding of the basic statistical principles and methods of modelling relationships between variables with focus on simple and multiple linear regression.
To enable participants to employ appropriate methods in analysing their data.
To develop a practical understanding of the principles of covariance, correlation, and simple and multiple linear regression.
To go beyond basic principles in order to understand the assumptions behind the models, the impact of violations, how violations can be diagnosed and possible solutions.
To develop an understanding on the reasons, use and implications of modelling categorical variables and interactions in linear regression analysis.
Course Content:
Covariance and correlation
Simple linear regression modelling (the dependent variable is a continuous variable)
Interpreting computer output
Model checking and model selection
Multiple regression modelling (the dependent variable is a continuous variable)
Handling categorical variables and interactions (as independent variables)
The course will have a strong practical emphasis, with regular sessions on computers enabling participants to work through examples in SPSS for Windows. The course does not cover logistic or multinomial regression (i.e. regression methods where the dependent variable is a binary or categorical variable). This will be the focus of the CASS course 'Regression Methods for Survey Data', which is run after this course.

Target Audience:
The course is aimed at researchers who need to perform basic statistical analyses on data from sample surveys, especially those in the social, economic, educational and medical sciences.

Pre-requisite:
Participants are expected to have a basic knowledge of simple statistical methods. They will previously have taken a course in introductory statistics and/or have completed Survey Data Analysis I (which is another CASS course run during the 2009/2010 programme at the University of Southampton). Ideally, course participants should be familiar with the following before undertaking Survey Data Analysis II.
*estimation based on random probability samples;
*formulation of testable hypothesis;
*standardised comparisons between groups using means and proportions;
*standard errors and confidence intervals;
*analysis of variance;
*SPSS statistical package.
The course will have a strong practical emphasis, with regular sessions on computers, using SPSS for Windows and real survey data, to enable participants to work through examples. The pace of presentation will be considerably faster than on Survey Data Analysis I, so that more ground is covered. For course participants not very familiar with SPSS there will be a prerequisite handout available to work through in their own time. For people not very familiar with the statistical methods please have a look at the preparatory reading list below.
Please bring a calculator for the workshops as well as a USB memory stick for saving your computer workshop output.

Please bring a calculator for the workshops as well as a USB memory stick for saving your computer workshop output.

The Instructor:
Olga Maslovskaya

Course Fee:
£25 per day for UK-registered students. £50 per day for staff from UK academic institutions (including research centres), ESRC funded researchers and registered charity organizations. £195 per day for all other participants. The course fee includes course materials, lunches and morning and afternoon tea, but not accommodation and travel which is to be arranged by the participant.