Measurement and Validity Lecture Notes

These flashcards cover the key concepts and definitions related to measurement and validity as discussed in Dr. Guidetti's lecture.

What is operationalization in psychological research?

Converting abstract concepts into measurable variables.

What are the four main levels of measurement?

Nominal, ordinal, interval, and ratio.

Define reliability in psychological measurement.

The consistency or stability of a measure.

What is validity in the context of measurement?

The accuracy of the measurement; whether it measures what it is intended to measure.

Explain the difference between independent and dependent variables.

Independent variables are manipulated by the researcher, while dependent variables are measured to see if they are affected by the independent variable.

What is the main purpose of hypotheses in research?

To specify testable statements about the relationships between variables.

What are some common sources of measurement error?

Instrumental error, participant error, and environmental error.

What types of validity are crucial in research?

Construct, content, criterion-related, internal, external, and statistical conclusion validity.

Why is it important to minimize measurement error?

Minimizing measurement error enhances the accuracy of research findings.

What is the difference between random and systematic error in measurement?

Random error is unpredictable and affects consistency, while systematic error consistently biases results.

Name two types of reliability assessment methods.

Test-retest reliability and parallel-forms reliability.

What does construct validity assess?

Whether a test measures the intended psychological construct.

How can bias in measurement occur?

Through content bias, construct bias, predictive bias, and method bias.

What key ethical principles should researchers consider?

Relevance, risk-benefit, cultural safety, consent clarity, data handling, and reciprocity.

Why is measuring psychological constructs challenging?

Because constructs like 'happiness' or 'anxiety' are abstract and cannot be directly observed.

What is the significance of the relationship between reliability and validity?

Reliability is necessary for validity; reliable data can still be wrong if it lacks validity.