27 Cards in this Set
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Keys to a good Hypothesis
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1. A comparison between variables
2. The relationship between variables is clearly specified & measurable
3. Unit of analysis is clear
4. It is testable
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Levels of analysis
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Nominal
Ordinal
Interval
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Reliability
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extent to which a measurement tool measures a concept consistently
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Validity
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extent to which a measurement tool measures the intended concept with accuracy
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Variable Name vs Variable Value
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VN = The unit of analysis > Religion
VV = a value of the named variable > Catholic, Protestant, Buddhist, Muslim, etc
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Nominal Level Variable
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communicates recorded differences of the between units of of analysis on the characteristic being measured correspond to numeric codes but codes have no inherent meaning
Eg religion
USE MODE
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Ordinal-Level Variable
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Values that can be ranked, able to distinguish relative amount, number and value can be assigned to a variable (e.g. 1 being lowest 4 being highest etc)
Eg strongly oppose - strongly agree or never - sometimes - always
USE MODE OR MEDIAN
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Interval-Level Variable
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Communicates exact differences between units of analysis
eg age measured in years 18, 24, & 77
USE MEAN MEDIAN OR MODE
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Mode
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The most common value of the variable
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Median
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the value of the variable that divides the cases right down the middle- with half of the cases having values below & half having values above the median
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Mean
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sum of all the cases individual values on a variable & divide by the number of cases
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Central Tendency
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the typical or average value
Mean, Median, or Mode
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Operationalization
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Describes explicitly how a concept will be measured
Identifies the procedures that will be used
Describes the metric that will be used
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The measurement process "operationalization"
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Concept -> precise definition of concept -> measurement strategy -> Variable
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Systematic error
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the measurement tool consistently mismeasures what we want it to measure
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Random error
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the measurement tool produces errors that are unpredictable and erratic
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Confounding/Alternative Variable
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another variable that may affect the value of the dependent variable
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Quazi-Experiments
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Research methods that seek to mimic conditions of a controlled experiment
They often exploit a naturally-occurring process
Researcher doesn't control Independent variable
e.g. political revolutions & their causes
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Quantitative
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(large N) controlled comparison, cross-tabulation, correlation analysis, linear regression, etc
broad, general claims. Not necessarily accurate in specific cases.
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Qualitative
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(small N) comparative method, case studies, process tracing, etc.
highly accurate claims about specific cases. Not generalizable.
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Observational Studies
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Observe the values of the independent and dependent variables in a sample of cases (observations)
Analyze the data to draw an inference about the relationship between the variables
Quantitative or Qualitative
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Forms Of comparison
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Cross Sectional
Longitudinal
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Dichotomous variable
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a variable that contains two categorizes
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Sufficient condition
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a factor whose presence guarantees an outcome will occur
If X, then always Y
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Necessary condition
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a factor that must be present for an outcome to occur
if no x, then no y
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Positive Relationship
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the lower value of the independent variable is associated with a lower value of the dependent variable
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Negative Relationship
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The lower value of the independent variable is associated with a higher value of the dependent variable
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PSC 202: Chapter 1