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Subject:

CASS Short Course - UK

From:

Jane Schofield <[log in to unmask]>

Reply-To:

Jane Schofield <[log in to unmask]>

Date:

Mon, 25 Feb 2002 14:02:11 -0000

Content-Type:

text/plain

Parts/Attachments:

Parts/Attachments

text/plain (112 lines)

Centre for Applied Social Surveys
Short Course:

Survey Data Analysis III

Supported by the ESRC
Dave Holmes and Nyovani Madise
24-26 April 2002
University of Southampton

CASS is an ESRC Resource Centre hosted by
the National Centre for Social Research, the University of
Southampton and
the University of Surrey
=============================================
=========
Course Objectives
•   To introduce participants to multivariate statistical
    methods for analysing survey data.

•   To provide hands-on experience of  analysing data
    using the statistical package SPSS.

Course Content
This course will include the following topics:
•     Logistic regression
•     Introduction to multinomial logistic regression
•     Principal component analysis
•     Factor analysis
•     Discriminant analysis
The course will include computer practicals so that
participants can work through exercises.

Target Audience
The course is aimed at researchers who need to analyse survey
data, especially those in the social, economic, educational and
medical sciences.  Participants should already be familiar with
basic statistical theory including inference and multiple
regression.

Pre-requisites:
This course is a follow on from Survey Data Analysis II,
13-15 March 2002.  Participants on this course must have prior
statistical knowledge covering regression modelling (up to the
level of Survey Data Analysis II).

Course Materials
Participants will receive course notes.

The Instructors
Dave Holmes is a Principal Experimental Officer in the Social
Statistics Department at the University of Southampton.  He
specialises in sample survey theory and statistical modelling.
He has taught courses on multivariate data analysis, survey
methods and statistical theory at both undergraduate and
master’s levels.
Nyovani Madise is the CASS Lecturer in the Social Statistics
Department at the University of Southampton.  She specialises
in the statistical analysis of large survey data.  She has taught
courses on multivariate data analysis and generalised linear
models at both undergraduate and masters levels.  Prior to
joining the University of Southampton she worked as a Lecturer
in Statistics at the University of Malawi.

Fee:
£400 (includes course materials, lunches and morning and
afternoon tea).  Because of ESRC support, a number of bursaries
are available which reduce the fee to £85 - applicants must be
full-time students, UK academic staff or ESRC-funded
researchers.

Location:
The course will be held at the University of Southampton.
During the course participants may be contacted via the
Department of Social Statistics (Tel: 023 80593048, Fax: 023
80593846).

Duration:
The course will begin with registration at 9.30 a.m. on
Wednesday,
24th April and end at 3.30 p.m. on Friday, 26th April 2002.
Recommended Reading:

For participants who wish to do background reading, the
following references may be useful.  Please note that although
reading is optional, participants who have little statistical
background are strongly advised to look at one of these
references.

•   Agresti, A.  An introduction to categorical data
    analysis, Wiley, 1996.

•   Kleinbaum, D.G.  Logistic regression: a self learning
    text, Springer, 1994.

*   Manley, B.F.J.  Multivariate statistical methods, Chapman
    and Hall, 1994.

Accommodation:
Please indicate on the registration form if you would like to be
sent details of local accommodation.  Participants are left to
book their own accommodation according to individual needs.

Deadlines and Refunds:
Course places are limited and early completion of this form is
recommended.  Payment must be made when submitting the
registration form.  Refunds for cancellation are as follows.  Full
refund for cancellation one month before the course, 90% if
cancellation is between 1 month and one week prior to the
course.  No refunds can be made for cancellations within 7 days
of the course start date.

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