Match List I with List II

List I	List II
A. Method of Difference	I. Assumption of experimental research
B. Law of single variable	II. Threat for experimental validity
C. While individual events cannot be predicated with accuracy, aggregate events can	III. Assumption of randomization
D. Interaction effect of testing	IV. Mill’s Canon

Choose the correct answer from the options given below:

Correct option is C

The correct matches are:
· A-IV: The Method of Difference is one of Mill’s Canons for causal inference, used to identify cause-and-effect relationships.
· B-I: The Law of a single variable is an assumption in experimental research, where only one variable is manipulated while others are controlled.
· C-III: The statement about aggregate events being predictable reflects the assumption of randomization in experiments, where large sample sizes help generalize findings.
· D-II: The interaction effect of testing is a potential threat to experimental validity, as prior testing can influence subsequent measurements.
Information booster:
1. Mill’s Method of Difference helps in identifying causal relationships by comparing cases where a phenomenon occurs and where it doesn’t, identifying factors that differ.
2. Experimental research relies on manipulating one variable while controlling others to isolate cause-and-effect relationships.
3. Randomization ensures that any differences in outcomes are due to the treatment rather than pre-existing differences between groups.
4. Testing effects can threaten the validity of an experiment if earlier tests influence the outcomes of subsequent tests.
Additional Knowledge:
· Mill’s Canons are a set of logical principles developed by John Stuart Mill to establish causality.
· Randomization is crucial for eliminating bias and ensuring that groups are comparable in experimental designs.
· Testing effects can be controlled by using methods such as counterbalancing or ensuring sufficient time between tests.
Key Points:
· Mill’s Method of Difference is widely used in experiments to isolate causality.
· Randomization is key to ensuring that experimental results are generalizable and not biased by pre-existing differences.
· Testing effects are an important threat to consider in experimental design, especially in longitudinal studies.