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Scholarly Inquiry in WF ED
11 November 2013
 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
 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)


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
 Information is desired about a populati0n

 But, data is usually from a sample

 Problem is to estimate population

parameters from sample statistics
 Level – What is typical?

 Dispersion – How much do entities vary?

 Relationship – Do variables covary?
Wfed550
Wfed550

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Wfed550

  • 1. Scholarly Inquiry in WF ED 11 November 2013
  • 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?