Experimental Research-Logic-Control & Variability

Experimental Research
The experimental method is a systematic and scientific approach to research in which the researcher
manipulates one or more variables, and controls and measures any change in other variables (Blakstad, 2008).
Why Psychologists conduct Experiments?
1) Researchers conduct experiments to test hypotheses about the causes of behavior.
2) Experiments allow researchers to decide whether a treatment or program effectively changes behavior
(Shaughnessy, E. B. Zechmeister, & J. S. Zechmeister, 2012).

Experimental designs in Psychology
Three types of experimental designs are commonly used
1) Independent measures (between groups)
2) Repeated measures (within groups)
3) Matched pairs (Mcleod, 2007).

LOGIC OF EXPERIMENTAL RESEARCH
   1) Researchers manipulate an independent variable in an experiment to observe the effect on
behavior, as assessed by the dependent variable.
     2) Control: Experimental control allows researchers to make the causal inference that the
independent variable caused the observed changes in the dependent variable. Control is the essential ingredient of experiments; experimental control is gained through manipulation,
holding conditions constant, and balancing.
       3) An experiment has internal validity when it fulfills the three conditions required for causal
inference: covariation, time-order relationship, and elimination of plausible alternative causes.
      4) When confounding occurs, a plausible alternative explanation for the observed covariation
exists, and therefore, the experiment lacks internal validity. Plausible alternative explanations are
ruled out by holding conditions constant and balancing.
      5) A true experiment involves the manipulation of one or more factors and the measurement (observation) of the effects of this manipulation on behavior. The factors the researcher controls or manipulates are called the independent variables. An independent variable must have at least two levels (also called conditions). One level may be considered the “treatment” condition and a second level the control (or comparison) condition.
  6) Experiments are effective for testing hypotheses because they allow us to exercise a relatively
high degree of control in a situation. Researchers use control in experiments to be able to state with confidence that the independent variable caused the observed changes in the dependent variable. The three conditions needed to make a causal inference are covariation, time-order
relationship, and elimination of plausible alternative causes. Covariation is met when we observe a relationship between the independent and dependent variables of an experiment. A time-order relationship is established when researchers manipulate an independent variable and then
observe a subsequent difference in behavior (i.e., the difference in behavior is contingent on the
manipulation). Finally, elimination of plausible alternative causes is accomplished through the use of control procedures, most importantly, through holding conditions constant and balancing.
When the three conditions for a causal inference are met, the experiment is said to have internal
validity, and we can say the independent variable caused the difference in behavior as measured
by the dependent variable (Shaughnessy et al., 2012).
Variability
All experimental data have variability that comes from several sources. Understanding these sources can
lead to improved experimental design and results.
Biological variation: Biological variation depends on the characteristics of the population being
studied. For example measuring the height of a random group of people will have a larger variability than a
study limited to people of one age or sex.
Process variation: It refers to variability in the data that is exhibited when the same sample is run
independently multiple times.
System Variation: System variation comes from the instrument used to take measurements. The variability of the measurement system contributes to the process variability and can be a common cause or a special cause.
Experimental variation
It is the total variation seen in an experiment and comes from both the process and biological population variability (SiRNAs Silencer, n.d.).