Hypotheses, Predictions, and Operational Definitions

The second step in the scientific method is stating a hypothesis: a testable prediction that derives logically from a theory.
A theory can generate many hypotheses; if more hypotheses related to a theory turn out true, the theory gains credibility.
Example: if social belonging is the key aspect of human functioning, predictions include that people who belong to social groups will be happier; or that individuals excluded by a group will be more aggressive.
Each hypothesis leads to specific predictions within a given empirical study.

The next step is to test predictions by conducting empirical research (collecting and analyzing data).
Design a study to test predictions; specifics of research methods are discussed later.
Regardless of the method, the first requirement is a concrete way to measure the variables of interest.

An operational definition provides an objective description of how a variable will be measured and observed in a study.
It eliminates fuzziness in thinking about a problem.
Example: to observe "kind behaviors" you need a consistent operational definition.
Before data collection, define how you will measure each variable to ensure reliability.
Variables to operationally define (examples): generosity, love, aggression, liberal, conservative, exhaustion, stress, attractiveness.
Practice: think of something interesting to study and how you would operationally define it.