Chapter 1 Key Terms Flashcards
Attribute ( 11 - 12 )
Category of a Variable; a possible score or value a Case may receive on a Variable
Cases ( 9 )
The subjects, participants, objects, or observations that make up a data set.
Census (22 - 23 )
When every element in a population is measured.
Constant ( 11, 20 )
A dimension on which the cases in a data set do not differ.
Continuous Variable ( 12 )
A Variable having a large, theoretically infinite number of Attributes.
Control Variable ( 20 - 21 )
A Variable whose influence on the Dependent Variable a researcher wants to eliminate or isolate to more correctly determine the influence of the Independent Variable on the Dependent Variable.
Covariation ( 21 )
The existence of a nonzero statistical relationship between two Variables; demonstrating covariation is one requirement for proving Causality.
Dependent Variable ( 19 - 20 )
In a relationship in which one Variable influences another Variable, the Dependent Variable is the one being influenced.
Dichotomy ( 11 )
A Variable having just two Attributes.
Discrete Variable ( 12 )
A Variable having a finite and usually small number of Attributes.
Ecological Fallacy ( 9 )
The Incorrect assumption that what is true about groups must inevitably be true of the members of those groups.
Element ( 22 )
A Member of a Population.
Independent Variable ( 19 - 20 )
The Variable that is doing the influencing.
Interval/Ratio ( 12 - 13, 16 - 18 )
Highest level of measurement; Attributes of a Variable cover ALL possibilities without overlapping and can be put in a natural order from low to high, as well as a numeric scale.
Level of Measurement ( 12 - 18 )
A classification system for variables based on the properties of a Variable’s Attributes; Nominal, Ordinal, and Interval/Ratio.
Net Effect ( 409 ? )
The effect of an Independent Variable on a Dependent Variable after other Independent Vairblaes have been controlled.
Nominal ( 10 )
Lowest Level of Measurement; Attributes of a Variable cover all possibilities without overlapping but cannot be put in a natural order from low to high.
Nonprobability Sampling Techniques ( 22 )
Methods of taking Samples in which not every Element in the Population has some chance of being selected or the probability of any particular Element being selected cannot be calculated.
Nonspuriousness ( 21 )
A nonzero Net Effect of one Variable on another even after all other Variables have been controlled; demonstrating Nonspuriousness is a requirement for proving Causality.
Open-Ended Attribute ( 17 )
An Attribute with no fixed lower limit or no fixed upper limit. Example: Seven *or more children. An IQ score of *less than 85.
Operational Definition ( 10 - 11, 18, 19 )
An explanation in concrete, specific terms of how a Variable will be measured.
Ordinal ( 12 - 16 )
Intermediate Level of Measurement. Attributes of a Variable cover all possibilities without overlapping and can be put in a natural order from low to high, but do not form a numerical scale.
Population ( 22 )
Group of entities about which a researcher would like to draw conclusions.
Probability Sampling Techniques ( 22 )
Methods of taking Samples so that every Element in the Population has some chance of being selected and the probability of any particular Element being selected can be calculated.
Reliability ( 18 - 19 )
Consistency of measurement. Cases assigned a particular Attribute on a Variable should be assigned the same or closely similar Attribute if they were measured after only a short interval of time. It is important that Operational Definitions be Reliable.
Sampling ( 22 - 23 )
The process by which a subset of Elements from a Population is selected.
Temporal Sequence ( 21 )
The order in time in which Variables occur or change values; which Variable happens first or changes first, which happens or changes second; establishing Temporal Sequence is a requirement for proving Causality.
Theoretical Definition ( 10 )
An explanation in abstract terms of what a researcher means by a certain Variable name.
Unit of Analysis ( 9 )
What the cases in a data set represent; common Units of Analysis are Persons, Families, or Nations.
Validity ( 19 )
Measuring what you intend to measure. Operational Definitions should be Valid - they should be measuring what the the Variable’s Theoretical Definition says the Variable is about.
Variable ( 9 - 10 )
A dimension on which the cases in a data set differ.
