Summary of Course:
The course focuses on the use of statistical modelling to study associations between variables. The course covers simple and multiple linear regression, where the dependent variable is a continuous variable. (This course is designed to follow the introductory CASS course Survey Data Analysis I. Course participants who have not attended this course can of course attend).
Course Objectives:
Course Content:
The course will have a strong practical emphasis, with regular computer workshop session enabling participants to work through examples in SPSS. The course will 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 also part of the CASS short course programme.
Target Audience:
The course is aimed at researchers who need to perform or interpret basic statistical analyses on data from sample surveys, especially those in the social, economic, educational and medical sciences. Participants may be researchers working in academia, local or central government, survey agencies, market research, the voluntary or the private sector.
Course Fees:
Thanks to continued ESRC funding we are able to offer this course at reduced rates as follows:
The course fee includes course materials, lunches and morning and afternoon refreshments. Travel and accommodation are to be arranged and paid for by the participant.
Course places are limited and early registration is strongly recommended.
Deadline and Refunds:
Course places are limited and early registration is strongly recommended. Please be aware that we will only hold a place without payment for a limited time.
Please refer to the terms and conditions of the University of Southampton online store when booking. An administration charge of £30 may apply for cancellations. No refunds can be provided for cancellations less than 28 days prior to the start of the course.
Location and Accommodation:
The course will be held at the Southampton Statistical Sciences Research Institute, Building 39, University of Southampton, Southampton, SO17 1BJ. Participants will need to make their own accommodation arrangements. Maps and travel information are available from the University of Southampton Travel Page. This also includes a map of the Highfield Campus. Building 39 is at the end of Salisbury Road edging onto Southampton Common.
Duration:
On the first day, the course will start with registration and coffee at 9.30 with formal teaching starting at 10.00 a.m; it will finish at about 5.45pm. On the last day, the course will start at about 9.30am and formal teaching will end at about 3.30p.m. Afterwards there will be an opportunity for participants to ask questions about the course and to discuss with the instructor how to analyse their own data (until about 4pm). (You can bring your own data to the course if you wish).
Pre-requisites:
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 (another CASS course). Ideally, course participants should be familiar with all or at least some of the following before undertaking Survey Data Analysis II.
The course will have a strong practical emphasis, with regular sessions on computers, using SPSS and real survey data, to enable participants to work through examples. 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 (to save outputs from the computer workshops).
Course Materials:
Participants will receive written course notes.
Please bring a calculator for the workshops as well as a USB memory stick in case you would like to save your computer workshop output.
The Instructors:
Dr Amos Channon is a Lecturer in Demography in the Division of Social Statistics and Demography at the University of Southampton. He has a BSc in Psychology from the University of Durham, and an MSc and PhD in Social Statistics from the University of Southampton. His research interests are in the analysis of large scale surveys to investigate child health and health inequalities in lower income settings, as well as the demography and health of the Middle Eastern region. He is on the British Society of Population Studies Council and has conducted training on survey data analysis to undergraduates, postgraduates and governmental organisations.
Dr Olga Maslovskaya is a Postdoctoral Research Fellow working on the ESRC-funded ‘The Use of Paradata in Cross-Sectional and Longitudinal Surveys' at the Southampton Statistical Sciences Research Institute (S3RI) at the University of Southampton. Olga holds an MA in European Policy and Politics from the Department of Government, University of Manchester and an MSc in Social Statistics - Research Methods from the Division of Social Statistics, University of Southampton. She also holds a PhD from the Division of Social Statistics, University of Southampton. Olga has been involved in the teaching of a wide range of statistical courses at both undergraduate and postgraduate level, as well as short courses for professional development in the UK and abroad.
Dr Gabriele B. Durrant is a Reader at the Southampton Statistical Sciences Research Institute (S3RI) at the University of Southampton. Her research interests include modeling of paradata, analysis of interviewer effects, nonresponse in sample surveys and multilevel modeling. She is currently the Principal Investigator of a 3.5 year ESRC funded research project on the ‘The Use of Paradata in Cross-Sectional and Longitudinal Surveys'. She previously was the PI of a 3.5 year ESRC funded research project on ‘Analysis of Nonresponse in Hierarchical Surveys'. She has published widely in the area of paradata and nonresponse. Gabriele teaches a wide range of statistical courses for professional development.
Preparatory Reading:
For those who would like to do some preparatory reading the following references may be useful. For participants particularly rusty or new to the methods covered preparatory reading is recommended.