Refresher course on Basic Statistics
A half-day course for PhD students and staff at the John Innes Centre
7th February, 2005 - JIC Genome Centre
AIMS: This half-day course is intended for those who are confident that they already have
an adequate knowledge of basic statistical ideas (standard errors, confidence intervals, ttests, simple regression methods), but want a short refresher to enable them to benefit
more fully from attending the intermediate statistics course “Experimental Design and
Analysis”.
PRE – REQUISITES: An adequate knowledge of basic statistical ideas (standard errors,
confidence intervals, t-tests, simple regression methods).
COURSE OUTLINE: This course will have short talks, question and answer sessions,
group work and discussions. The facilitators will cover all the material included in the first
two days of the “Basic Statistics and Design Principles” course, providing you with an
overview of the key concepts involved.
NOTE: Participants will be working in groups of about 4 for discussions and practical work.
One computer with Genstat already loaded, has to be available for each group. The
required data sets will be sent in advance and should also be loaded.
Timetable
S1
9.15 - 10.15
Introduction, exploratory data analysis (EDA), relating the analysis to
the objectives. The session will be interspersed with practical work
on Genstat.
S2
10.15 - 11.55
Basic concepts of statistical inference – with practical work on Genstat
and group discussions. Participants will take a brief break for tea or
coffee during this session.
S3
11.55 - 12.45
Regression ideas, including practical work
S4
12.45 - 1.00
Discussion, overview and feedback
1
Experimental Design and Analysis
A course for PhD students and staff at the John Innes Centre
7 – 9 February, 2005
JIC Genome Centre
PRE – REQUISITES: An adequate knowledge of basic statistical ideas (standard errors,
confidence intervals, t-tests, simple regression methods) and good familiarity with the
statistics software package Genstat. This may be obtained by attending the refresher
course or the basic statistics course held in early December 2004.
NOTE: Participants will be working in groups of 2 for discussions and practical work. One
computer with Genstat already loaded, has to be available for each group. The required
data sets will be sent in advance and should also be loaded. Please also bring along a pen
and a calculator.
Timetable
DAY 1 - EXPERIMENTAL DESIGN IDEAS
S1
2.00 - 2.15
Introduction to the course and to the experimental game
“TOMATO”
The aim of the game is to get participants to think about
experimental design ideas – in particular, of replication,
randomisation, treatment factors, and blocking, while at the same
time reviewing their knowledge of basic statistical methods. (RDS)
P1
2.15 - 3.00
TOMATO: Experiment 1
This is the first of two experiments which participants will be asked
to design. This first one is simple but the next is less so.
Participants (working in pairs) will design the experiment – and
then collect the relevant data. Participants will then look at the
data in a descriptive fashion and come to some conclusions. (SA)
S2(a) 3.00 - 3.40
3.40 - 4.00
Discussion
The design approaches will be discussed, and data from the
TOMATO game used to review ideas of basic statistical methods.
(SA)
Tea
S2(b) 4.00 – 4.45
Review of ANOVA ideas using TOMATO data (RDS)
P2
Designing Tomato – the real experiment
Here participants will be asked to ignore previous results from the
TOMATO game and to design the "real" experiment, bearing in
mind that another experiment can be done in year 2. They will
then collect the data and descriptively study the results from Year
1 and come to some conclusions to address the experimental
objectives. (RDS)
4.45 - 6.00
2
DAY 2 - GENERAL LINEAR MODELS
S3
9.30 – 10.30
Introduction to Linear Models
Illustrative examples will be used to introduce participants to the
concept of a Linear Model which underlies all standard analysis of
variance and multiple regression techniques. This is important
background to developing an understanding of more general forms
of the analysis of variance, e.g. when the response variate is
believed to be influenced by a number of factors as well as
covariates (or regressor variables). (SA)
10.30 - 11.00
Coffee
S3
11.00 - 11.30
Introduction to Linear Models (Continued …)
S2(c)
11.30 – 12.15
Discussion of design of Experiment 2 and participants'
findings
This session will include a demonstration of a non-orthogonal twoway analysis of variance on Genstat. (RDS)
P3
12.15 – 1.00
Practical work on fitting Linear Models (SA)
1.00 – 2.00
LUNCH
2.00 - 3.00
Dealing with data structures involving both grouping variables
(factors) and quantitative variates. (SA).
3.00 - 3.15
Using Genstat and interpreting output from a General Linear Model
(SA)
3.15 - 3.45
Tea
3.45 - 4.30
Assumptions underlying the analysis of variance. (RDS).
4.30 - 5.30
Dealing with covariate information. Practical work to
illustrate the analysis when the response variate is influenced by
both factor variables and by regressor variables. Residual analysis
will also be considered. (SA).
3
DAY 3 - GENERALISED LINEAR MODELS AND DESIGNING EXPERIMENTS
IN SMALL BLOCKS
Dealing with non-normal data, i.e. using Generalised Linear
Models. (RDS).
S6
9.30 - 10.30
P6
10.30 -11.00
Practical work with binary data.
11.00 - 11.30
Coffee
S7
11.30 - 12.00
Further ideas in Generalised Linear Models. (SA).
P7
12.00 - 1.00
Further practical work.
1.00 – 2.00
LUNCH
2.00 - 3.00
Designing experiments in small blocks
S8
Principles involved in designing experiments in small blocks will be
illustrated. There will also be an overview of alpha-designs,
relevant to experiments involving large numbers of plant
genotypes and of augmented designs, in which most genotypes
are trialled only once, but a few controls are tested many times
(relevant e.g. to genetic analysis where only limited seed of
progeny is available but unlimited amounts of the parents).
(SA/RDS).
P8
3.00 - 3.30
Practical work on design using Genstat.
3.30 - 3.45
Tea
3.45 - 4.45
Case studies and practical applications
Volunteer participant will briefly outline one of his or her own
experiments, relating it to course material. This will be followed by
a discussion of the examples presented. (RDS to lead discussion).
4.45 - 5.00
Feedback and completion of assessment forms
Teaching/demonstrating staff:
SA
LA
AM
RDS
-
Savitri Abeyasekera
Lia Arraiano
Andreas Magusin
Roger Stern
4