The document discusses the key aspects of experimental design, including recognizing the problem, choosing factors and levels, selecting a response variable, designing the experiment, performing it, analyzing data, and concluding results. It provides an example of a simple experiment testing the effect of temperature on the rate of a chemical reaction. The document emphasizes principles like replication, randomization, and blocking to control for nuisance factors and minimize inaccuracy.

1. Experimental design
Dr Richard Goodey
SEMS
4/5/2012 Researcher’s Development Day

2. What is an experiment?
• A test
– To find out something about a process
– More specifically, usually a series of tests
• Something we do all the time in our everyday
lives
• In this context, most relevant to physical and
social sciences
• In these fields, most PhD candidates and
researchers do some sort of experiment
4/5/2012 Researcher’s Development Day

3. A simple example
• What is the effect of temperature on the rate
of reaction between limestone and acid?
• 2HCl + CaCO3 -> CaCl2 + H2O + CO2
• So this should be simple?
• Add limestone to acid, measure the volume of
gas produced in one minute (e.g.)
4/5/2012 Researcher’s Development Day

4. Results
120
100
Vol of carbon dioxide (cc)
80
60
40
20
0
0 10 20 30 40 50 60 70 80 90 100
Temperature (°C)
• Have we answered the question?
4/5/2012 Researcher’s Development Day

5. General model
Controllable factors
x1 x2 xn
Input Process Output
z1 z2 zn
Uncontrollable factors
4/5/2012 Researcher’s Development Day

6. Our simple experiment………?
• Temperature control
• Concentration of acid
• Volume of acid
• Mass of limestone
• Size of limestone particles
• Mechanism for measuring gas volume and time
• Purity of reagents
• Atmospheric pressure
4/5/2012 Researcher’s Development Day

7. Basic principles
• Replication
– Not to be confused with repeated measurement
• Randomisation
– Design against unknown nuisance factors
• Blocking
– Eliminate or reduce known nuisance factors
4/5/2012 Researcher’s Development Day

8. Guidelines for design
• Recognise and state the problem
• Choose factors, range and levels
• Select response variable
• Design experiment
• Perform experiment
• Analyse data
• Conclude and recommend
4/5/2012 Researcher’s Development Day

9. Things to note
• Keep the design and analysis as simple as
possible
• Practical vs statistical significance
• Experiments are iterative and repetitive
4/5/2012 Researcher’s Development Day

10. Experiment with a single factor
• Recognise and state the • What is the strength of
problem fibres used to make
shirts?
• Choose factors, range • Influenced by weight
and levels percent of cotton in
fibre. Range between
10 and 40 percent.
Levels 15, 20, 25, 30
and 35%
• Select response variable • Tensile strength
4/5/2012 Researcher’s Development Day

11. Design experiment
• Utilise replication and randomisation
• Replication = 5 samples per level, total
number of tests therefore 25
• Randomisation:
Cotton Experimental run number
weight %
15 1 2 3 4 5
20 6 7 8 9 10
25 11 12 13 14 15
30 16 17 18 19 20
35 21 22 23 24 25
4/5/2012 Researcher’s Development Day

12. • Use a process to put those in random order
Test sequence Run number Cotton weight %
1 8 20
2 18 30
…… …… ……
25 3 15
• Minimises unknown nuisance factors
4/5/2012 Researcher’s Development Day

13. Perform the experiment, collect data
30
25
Tensile strength (psi)
20
15
10
5
0
0 5 10 15 20 25 30 35 40
Cotton weight %
• Now we need to perform some data analysis
to assess significance etc
4/5/2012 Researcher’s Development Day

14. Summary
• Performing an experiment is maybe not so
straightforward as it seems?
• Careful planning will minimise:
– Inaccuracy
– Time wasted
• Some level of statistical analysis will be
required to prove or disprove your hypothesis
4/5/2012 Researcher’s Development Day