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it's true because its always been true
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something is true because it is self evident (resist efforts to test advertising methods)
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belief is something because of a trusted source; parent or teacher
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general areas of investigation
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testable statements about relationship variables
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variable that creates a possible but incorrect explanation of results
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must be selected randomly and tested for homogeneity to ensure results are not due to type of sample used
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systematically varied by researcher "causes" dependent effect
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are observed and valued presumed to depend on effects of the independent variable
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classify people or objects by name or number. Social, license
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ranked smallesg to largest (horserace with out stop watch)
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numbers used but no true zero. Temperature and IQ. Can't say twice as intelligent.
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same as interval but true zero.
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consistency of your measure
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are we measuring what we think we are measuring
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appears to measure waht we think its measuring
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check measure against existing and similar measures
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if predictor relates to outcome as expected
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choose groups known to possess property in question-give to another group not known to have property then compare
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Term
| 3 ways to check reliability |
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Definition
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stability=test/retest (1 test given at two different times)
internal consistency= all items measuring same concept
equivalancy=two parallel forms
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1.0 is perfect
.90-.80 very good reliability
.79-.70 good/fair
under .70=not good
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| 3 ways to increase reliability |
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increase # of items in measure
reduce the ambiguity of your items
discard "bad" items
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all the elements pertinent to a study
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that from which a sample will be taken
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randomly selected and equal chance
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chosen o the basis of same type of criteria
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simple random sample, systematic random sample, stratified random, plus 1 random sampling, random digit dialing
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numerical characteristics of a sample (we know)
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numerical characteristics of a population (we never know this)
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the probability that a given interval actually contains the true pop parameter (68% probability)
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an interval within which we think the true population parameter lies
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