1. B A S I C
P R I N C I P L E S
I N
E X P E R I M E N TA L
D E S I G N S
2. BASIC PRINCIPLES IN EXPERIMENTAL
DESIGNS
• An experimental design may be defined as simply a sequence of steps (taken ahead of time), which permit the objective
analysis of objective data in a way that a definite cause-effect relationship can be inferred between the independent variable
and the dependent variable.
• An independent variable is defined as the variable, which is manipulated by the experimenter either directly or through
selection, so that its effects can be studied upon the behavioural measure. The variable is so named because we can change it
independently.
• A dependent variable is the response variable or the behavioural measure, which is affected by the manipulation of the
independent variable. The variable is so named because responses depend upon those changes or manipulations.
• Suppose, for example, the experimenter is interested in studying the effect of the intensity of illumination upon retinal fatigue.
Obviously, in this situation the experimenter would change the levels of intensity of illumination and would see how long the
subject is able to read under each level. In this example, the intensity of illumination is the independent variable and retinal
fatigue is the dependent variable.
3. ACCORDING TO OSTLE &
MENSING (1975, 260),
THERE ARE THREE BASIC
PRINCIPLES OF AN
EXPERIMENTAL DESIGN:
1. REPLICATION
2. RANDOMIZATION
3. LOCAL CONTROL
4. REPLICATION
• The term replication is really a fusion of two words, namely,
duplication and repetition
• It refers to the deliberate repetition of an experiment, using
a nearly identical procedure with a different set of subjects,
in a different setting and a different times.
• According to the Principle of Replication, the experiment
should be repeated more than once. By doing so the statistical
accuracy of the experiments is increased.
5. • For example, If we need to compare the grain yield of two varieties of wheat then each variety is
applied to more than one experimental unit. The number of times these are applied to experimental
units is called their number of replication.
• Replication provides an efficient way of increasing the precision of an experiment. The precision
increases with the increase in the number of observations.
• Replication permits a person in revalidating a previous study or raises some questions about the
previous studies.
• Thus, replication provides a very accurate estimate of the experimental error that can be used as a
basic unit of measurement in evaluating the significance of the observed differences.
• Experimental error refers to the errors occurring due to faulty experimental design, faulty
measurement, biased observation, uncontrolled variations among the experimental units (or subjects)
and the uncontrolled extraneous variables.
• At the end, it must also be added that replication should not be confused with multiple measurements.
Suppose the experimenter selects a particular level of intensity of light and experiments its effect
upon the retinal fatigue of several subjects one after another. This is obviously not a case of
replication but a case of multiple measurements.
6. RANDOMIZATION
The principle of randomization involves the allocation of
treatment to experimental units at random to avoid any bias in
the experiment resulting from the influence of some
extraneous unknown factor that may affect the experiment.
7. • Each statistical test used in an experimental situation depends upon some assumptions of which the most
frequent and common assumption is that the observations should be independent.
• The independence of the observations is maintained when the samples are randomly drawn from the
population or the subjects are randomly assigned to the experimental treatments.
• Thus randomization ensures the independence of the observations which, in turn, makes a statistical test
valid.
• Not only this, when subjects are randomly assigned to the experimental treatments or the experimental
treatments are randomly assigned to subjects, this automatically controls the extraneous variables, which,
otherwise, are left uncontrolled.
• Sometimes it has been found that complete randomization becomes difficult.
• This is especially true when one is dealing with organismic variables (Any characteristic of the research
participant/individual under study that can be used for classification Such as personal characteristics of
gender, height, weight, age, etc.)
• In such a situation, the experimenter should not insist on complete randomization but a middle path
between complete randomization and complete nonrandomization or systematization should be followed.
8. LOCAL CONTROL
Local control focuses on increasing experimental precision
through the exercise of control over extraneous variables. This
is a refined technique that aims at reducing external
influence to a much higher level than replication or
randomisation.
9. • By local control we mean the amount of balancing, blocking and grouping of the subjects or
the experimental units employed in an experimental design.
• Grouping : The term grouping is most easy to define. It refers to the assignment of
homogeneous subjects or experimental units into a group so that different groups of
homogeneous subjects may be available for differential experimental treatments.
• Blocking : Blocking refers to the assignment of experimental units to different blocks in such a
manner that the assigned experimental units within a block may be homogeneous.
• Balancing : Balancing in an experimental design refers to the fact that grouping, blocking and
assignment of experimental units to the different treatments have been done in such a way that
the resulting design appears to be a balanced one.
• A design to be statistically and experimentally sound must possess the property of local control.
10. Reference
Singh, A.K.(2019).Tests, Measurement and Research in Behavioural Sciences (6th ed.).
Bharathi Bhavan.
Kothari, C.A.(2019). Research Methodology methods and techniques(4th ed.). New age
International Publishers.
