Causal research designs aim to determine cause-and-effect relationships. Scientifically, a cause only increases the likelihood of an effect rather than guaranteeing it, and causation can never be proven with full certainty. For a variable to be considered a causal factor, it must meet three conditions: concomitant variation with the effect, temporal precedence of the cause, and elimination of other possible explanations. Experimental designs involve manipulating an independent variable to observe its impact on a dependent variable, while controlling for extraneous variables, and can be classified as experimental, quasi-experimental, or pre-experimental based on their use of control groups and random assignment.

1. Causal research
Design

2. Concept of Causality
Ordinary meaning Scientific Meaning
X is the only cause of Y X is only one of a number of possible
causes of Y
X must always lead to Y The occurrence of X makes the
occurrence of Y
It is possible to prove that X is a cause
of Y
We can never prove that X is a cause
of Y. At best, we can infer that X is a
cause of Y

3. Conditions for Causality
• Concomitant Variation
• Time order of occurrence of variables
• Elimination of other possible causal factors

4. Concepts
• Independent variables/ treatments
• Test Units
• Dependent variable
• Extraneous variable
• Experiment
• Experimental design

5. Classification of Experimental
Design
Experimental
design
Pre
experiment
al
One short
case study
One group
pre test
post test
Static
Group
True
experiment
al
Pre-post
control
group
Post test
only
control
group
Quasi
experiment
al
Time series
Multiple
time series
Statistical
Randomize
d
Factorial