Definition of Terms

A.  Operational Definition:  The definition of a variable in terms of operations needed to produce or measure that variable.
Variable:  Any characteristic or quality that can take on two or more values. Opposite to a constant, which is ay characteristic or quality that can take on only one value.  

B. Measurement Scales:  The information yielded by a measurement operation (NOIR).
Nominal:  Information about whether two values are the same or different.
Ordinal:  Information about whether two values are different and the direction of the difference. 
Interval:  Information about the units that mark the difference between two values.
Ratio: Information about the relation between two values by their distance from a fix zero-point

C.  Measurement Reliability: The consistency of repeated measures of the same phenomenon with the same device across experimenters and/or time.

D.  Measurement Validity: The validity of a measuring device to assess  what it supposed to assess (i.e., its truthfulness).
Face Validity: The appearance that a measurement device measures what it is supposed to. 
Criterion-Related (Concurrent) Validity: Correlation with other established measurement devices
Predictive Validity: Correlation with some future behavior.  
Construct Validity: Assessment from many studies that the device measures many aspects of the 
                    concept it is supposed to be measuring  

E.  Dependent Variable (sometimes called criterion variable):  The target variable. The variable that is the the cause of, predicted by or the result of other variables.  
 
F.  Independent Variable (sometimes called predictor variable): The manipulated variable.  The variable you are interested in whether variation in it is associated with or causes variation in the the DV
F1.  Subject Independent Variable:  An IV that is a characteristic or trait of participants.
F2. True Independent Variable:  An IV that can be randomly assigned to participants.

G.  Hypothesis:  Operationally defined hypothetical statement that specifies a predicted relation (causal, correlational) between the IV and DV.

H. Extraneous Variable(s): The variable(s), associated with the IV, that influence the DV. Such variable(s) may be brought under experimental (or statistical) control 

I.  Experimental Control:  The extent to which the design of an experiment does not permit extraneous variables to influence the dependent variable by holding EV constant across levels of the IV or through randomization.

J.  Internal Validity:  The extent to which the design adequately tests the hypothesis.  Inadequate tests of hypotheses may results from poor operationalization of the variables, lack of validity or reliability of the measures, or the lack of experimental control.

K.  External validity:  The extent to which you feel sure that the results obtain can generalize to other subjects...
A) who are in other settings			
B) who are measured using other instruments,
C) who are studied by other experiments using other measures
D) who are living at other times.  		
E)  who ...etc.