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Linear Models in Statistics Module Handbook 2015-16
Linear Models in Statistics
Autumn Teaching Period 2015-16: Masters Level Module 976C8
Module Organiser: Prof Alan Garnham, PEV 1 2B12, [email protected]
Statistics are about describing the appropriate patterns in data to others using
numeric, graphic, and verbal forms of communication.
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Linear Models in Statistics Module Handbook 2015-16
Official Module Title: Linear Models in Statistics
Official Module Code: 976C8
Module Convenor: This module is convened by Alan Garnham, who is a member of the
School of Psychology. This document was prepared by Alan Garnham and you are welcome
to direct queries about the module to him during his office hours (see Student Consultation
Times on Sussex Direct) in 2B12 (Pevensey 1 Building), by phone (x8337) or email
([email protected]).
Type of Module: Linear Models in Statistics is a Masters-level module, compulsory for all
Psychology students taking the MRes in Psychological Research Methods, the MSc in
Applied Social Psychology, the MSc in Cognitive Neuroscience, and the MSc in Foundations
of Clinical Psychology and Mental Health. Attendance is usually required for Psychology PhD
Students who have not taken this module or an equivalent module before (students should
agree with their supervisor and the Director of Doctoral Studies a package of research
methods modules before they begin their PhD). The module is one of the core research
methods modules for Psychology Masters students.
Credits: Linear Models in Statistics is a 15 credit module.
Prerequisites: None
School Ownership: Psychology
Aims and Objectives:
Linear Models in Statistics consist of a series of lectures and computer classes, mainly
aimed at introducing or re-introducing postgraduate students to ANOVA, regression and
related linear modelling techniques, and training them to use SPSS, a popular statistical
analysis package, to carry out the corresponding analyses. A single topic will be covered in a
lecture and SPSS class each week. Details of the topics are on Page 3.
More specifically, students who have completed the module should:
1. Be able to analyse data from behavioural studies, in particular those calling for
regression, ANOVA and related techniques (general and generalised linear modelling).
to understand why and when certain procedures are used.
to use SPSS to carry out the analyses.
to interpret the results (and the output of the SPSS analyses) properly.
2. Be able to communicate results from data analysis.
3. Be able to understand the results of other people’s research.
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Linear Models in Statistics Module Handbook 2015-16
Teaching: There is one lecture a week in weeks 1 – 11 and one computer class. In the
SPSS sessions you will go through a number of exercises, following detailed instructions in a
handout, using SPSS on a desktop computer. The module organiser and demonstrators will
be available to assist you through the exercises, provide verbal feedback on your work, and
answer any other questions about the module that you may have. The practical classes are
designed to follow the lectures. In week 6, the lecture will introduce the take-away
assignment, which will be due in at the end of the Autumn Teaching Period (official details of
the submission date will be on Sussex Direct). The computer session in that week can be
used to start work on the assignment or for revision and supplementary help.
In week 12 there will be no lecture and the computer class will be replaced by a three-hour
session in which the demonstrators will help you work through a mock exam and provide
verbal feedback on your attempts to answer the questions in it. The exam proper will be in
the Assessment Period following the Christmas Vacation (you have I hour and thirty minutes
for the real exam).
To recap, in week 1 there is an introductory lecture followed by a 2-hour computer-based,
session to (re)introduce you to data entry and graphing techniques in SPSS. In weeks 2 to 5
and 7 to 11 there is a one-hour lecture and a two-hour computer session on a particular
statistical technique. The lectures and the computer sessions will both be given by Alan
Garnham. Demonstrators will help with the computer sessions. In week 6 the take-away
assignment will be introduced, and in week 12 there will be a mock exam. The real exam is
in the Assessment Period after Christmas. Please note that official timetabling details
should be found on Sussex Direct, which should be regarded as the definitive source
of information.
Supplementary Sessions: In addition to the main teaching sessions mentioned above,
there will be other sessions primarily designed from those who have been away from higher
education for sometime, who do not feel confident about statistics, or who are unfamiliar or
relatively unfamiliar with SPSS.
One such session will be a lecture in Week 2. This lecture will provide a recap of some basic
mathematical and statistical concepts and notation that you need to be familiar with, and will
be accompanied by pointers to where to find additional help, if you do not feel completely
comfortable with these ideas.
The second set of sessions, which will be one place where you can find, among other things,
more help and feedback on your understanding of basic maths and statistics, is a set of drop
in sessions, where you can consult, one-on-one, or in small groups of 2-5, with one of the
demonstrators. These sessions will be scheduled, if possible, on Thursdays or Fridays. Each
session will be run by one of the demonstrators, and they will take place in about 9 weeks of
the Teaching Session (linked to weeks in which substantial topics are taught in the lectures
and classes. Details of the weeks when and the place where these sessions will be held will
be announced later. Depending on the popularity of the sessions, we may introduce a
booking system for 5 or 10 minute appointments.
I will also be available in my office hours to answer questions about the course material.
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Linear Models in Statistics Module Handbook 2015-16
Summary of Topics
Week 1
Introduction to Module
Introduction to SPSS
Week 2
Additional Lecture on Basic Maths and Statistics
Week 2
Simple Linear Regression
Week 3
Multiple Regression
Week 4
t-tests
Week 5
ANOVA
Week 6
Assignment
Assignment / Revision
Week 7
Mixed ANOVA + ANCOVA
Week 8
MANOVA
Week 9
Logistic Regression
Week 10
2 and Log-Linear Modelling
Week 11
Multi-Level/Mixed Effect Models
Week 12
Mock Exam
Post-Christmas Assessment Period
Real Exam
Please note that information about the time and place of the Real Exam will be released as
part of the University’s Exam Timetabling.
Contact Details
Alan Garnham (AG), Pev1 2B12, [email protected]
Demonstrators – tba
Any queries outside of the teaching sessions should be addressed to Alan Garnham, by
email, in his office hour, or by appointment.
Apart from being available in the SPSS classes and running the drop-in sessions, it is not
part of the demonstrators’ duties for this model to answer student questions.
Module handouts and data
In each SPSS seminar you will be given a handout that will contain a number of exercises for
you to work through. In some weeks you will have to type your own data in, but normally you
will be able to get the data (and the handouts) from the module webpages on Study Direct.
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Linear Models in Statistics Module Handbook 2015-16
You can access these pages on and off-campus but in both cases you will need your Sussex
ID and Password. You can save your data and output (very useful when revising for the
exam) to your N-drive. Answer sheets for those people who wish to continue working through
the handouts after the class has finished will be provided after the class on a particular topic
has run.
Assessment:
There are two pieces of formally assessed work for this module, an open book exam in the
University Assessment Period immediately after the Christmas vacation and a written
assignment (to be submitted before Christmas). Each counts for 50% of the final assessment
for Linear Models in Statistics.

Open Book Exam (50% of the final assessment):
o The exam will take place in the University Assessment Period following the
Christmas Vacation– please check Sussex Direct for exact place and time.
Please note, also, that if you need to plan your Christmas travel early, you
may have to do so before the exact date of the exam is known.
o It will be a 1 hour 30 minute written exam that will contain three questions. The
first question will be compulsory and you will be able to choose between the other
two. For each question you will be presented with an experimental or other
empirical scenario and some SPSS output that you will need to interpret. The first
question is worth 40% of the mark for the exam and the other question you
answer is worth 60%.
o The final session of the module (Autumn Teaching Period week 12) will be
dedicated to running through a practice exam to give you an idea of what to
expect. This will be very informal and you will be able to chat amongst yourselves
and ask the demonstrators as many questions as you want!

Assignment (50% of the final assessment):
o The aim of this assignment is to demonstrate that you can analyse data
appropriately and write it up as if it were an actual results section that could be
published in a journal.
o You will each be given a SPSS data file later in the term. You will need to analyse
the data in this file, selecting appropriate analyses from the techniques that we
will cover in the module.
o This assignment should include three sections: (1) a brief introduction in which
you state the hypotheses you have chosen to test, the statistical tools you have
chosen to use (and why), (2) an actual results section including appropriate
graphs and/or tables, and the interpretation of the statistical analysis, (3) a very
short conclusion including a summary of what the results actually tell you.
o The maximum word count for this assignment is 1,000 words, however part of
the art of writing a results section is to include all of the relevant and important
information, but to also make it as concise and snappy as possible. This can be
quite a difficult balance to achieve and your marks will be based in part on how
well you succeed, so a lengthy assignment will not necessarily gain you any more
marks!
o You can discuss the assignment with other people taking the module, but your
submission must be entirely your own work, otherwise you risk being charge with
misconduct (specifically collusion) and you may lose some or all of the marks for
this piece of work. See http://www.sussex.ac.uk/s3/?id=33
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for more details of the University’s policy on plagiarism and collusion. In particular,
there is considerable choice in the assignment for which analyses are reported,
and it is unlikely that two students working independently would produce exactly
the same set of analyses.
Information on the following can be found at the link below:
 submitting your work
 missing a deadline
 late penalties
 MEC – mitigating evidence
 Exams
 Help with managing your studies and competing your work
 Assessment Criteria

http://www.sussex.ac.uk/psychology/internal/students/examinationsandassessment
Student Feedback: Student feedback is by module questionnaire. Informal comments are
also welcome throughout the module. As an example of our response to student feedback,
answer sheets for the class exercises were requested by students and we have provided
them for the last three years.
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Linear Models in Statistics Module Handbook 2015-16
Reading Lists
For Statistical Methods
As an intermediate level text, we recommend
Howell, D. C. (2012). Statistical methods for psychology (8th edition). Belmont, CA.:
Wadsworth. [Earlier editions in library at QZ 210 How]
Another very good book with a different approach, very good at explaining underlying
principles, is:
Everitt, B. S. (1996). Making sense of statistics in psychology. Oxford: Oxford University
Press. [not in library]
If you find Howell (and/or Everitt) too daunting, there are many introductory statistics book,
including your undergraduate texts!!, or try either of these books by our ex-colleague, Dan
Wright.
Wright, D. B. (1997) Understanding statistics: An introduction for the social sciences.
London: Sage. [HB 320 Wri]
Wright, D. B. (2002). First Steps in Statistics. London: Sage Publications. [QD 3200 Wri]
For SPSS
Field, A. P. (2013) Discovering statistics using IBM SPSS Statistics (4th Edition). London:
Sage Publications. [Earlier editions in library at QE 1927 SPS (FIE)]
Pallant, J. (2013) SPSS Survival Manual (5th Edition). Maidenhead: Open University Press,
[QE 1927 SPS (PAL)]
Brace, N., Kemp, R. & Snelgar, R. (2012) SPSS for Psychologists: a guide to data analysis
using SPSS for windows (5th Edition). Basingstoke: Palgrave Macmillan. [Earlier
editions in library at QE 1927 SPS (BRA)]
For Reporting the Results of Research
Field, A. P. And Hole, G. J. (2003) How to design and report experiments. London: Sage [QZ
200 Fie].
Sternberg, R. J. (1988). The psychologist's companion: A guide to scientific writing for
students and researchers. 2nd ed. C.U.P. [BF 76.8 Ste]
Sternberg, R. J. (Ed.) (2000) Guide to publishing in psychology journals. Cambridge:
Cambridge University Press
Wright, D. B. (2003) Making friends with your data: Improving how statistics are conducted
and reported. British Journal of Educational Psychology. 73, 123-136.
Wilkinson, L. and the Task Force on Statistical Inference, APA Board of Scientific Affairs
(1999). Statistical methods in psychology journals: Guidelines and explanations.
American Psychologist, 54, 594-604. It is available on
http://www.apa.org/journals/amp/amp548594.html.
On Writing More Generally
Strunk, W. Jr. & White, E. B. (1979). The elements of style (4th Ed.). Needham Heights, MA.:
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Allyn & Bacon. [PF 291 Str].
For some of the books, the library also has copies of earlier editions, which you may find
useful if the copies of the latest edition are on loan. Remember authors sometimes change
chapter numbers between editions!
Specific Topics
Most of the topics are discussed in any intermediate level statisitics texts, including Howell,
and some are discussed in introductory texts. Note that Howell only discusses MANOVA as
an approach to repeated measures designs, and not more generally. Field has a chapter on
MANOVA.
Three useful references on specific topics are:
Power
Cohen, J. (1992). A power primer. Psychological Bulletin, 112, 155-159. [QZ 10 Psy].
ANOVA as regression – the origins of the General Linear Model
Cohen, J. (1968). Multiple regression as a general data-analytic system. Psychological
Bulletin, 70, 426-443. [QZ 10 Psy]
This was one of the first papers in the psychology literature to point out that ANOVA is really
just a regression. In typical modesty, Cohen stresses that this was not a new idea of his.
Contrasts in ANOVA
Rosenthal, R. & Rosnow, R. L. (1985). Contrast analysis: Focused comparisons
in the analysis of variance. Cambridge: Cambridge University Press. [QZ 210 Ros]