2. Measurement – Assigning numbers to
phenomena according to rules
Research Design – Collecting and
organizing data to reveal relationships and
causation
Data Analysis – Inspecting, cleaning,
transforming, and modeling data to
discover useful information
3. Variables – Attributes that can take on two
or more mutually exclusive values
Variables describing entities are measured
Measurement involves the interaction
between a measurement instrument and
the entity measured
Measures can be manifest or latent
Measures must be reliable (accurate) and
valid (have meaning)
4.
A and B must covary
A must precede B
A, and only A, must be
the cause of B
Covariation –Changes in
cause must be changes
in the effect
Temporal Precedence —
Changes in the cause
must precede changes
in the effect
No plausible
alternatives — Changes
in cause are only
explanation for effect
5. Information is desired about a populati0n
But, data is usually from a sample
Problem is to estimate population
parameters from sample statistics
6. Level – What is typical?
Dispersion – How much do entities vary?
Relationship – Do variables covary?
