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13 Cards in this Set

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Paramertic Statistics
Involve numbers with known, continuous distribution. Appropriate when the data is interval or ratio scaled and when the sample size is large
Nonparametric Statistics
Appropriate when the variables being analyzed do not conform to any known or continuous distribution
T-Test
A hypothesis test that uses teh t-distribution. Univariate t-test is appropriate when the variable being analyzed is interval or ratio
Degrees of Freedom
The number of observations minus the number of constraints or assumptions needed to calculate a statistical term
Nominal Variables
Mutually exclusive but not ordered categories
Ordinal Variable
The order matters but not the diffirence between variables
Interval Variable
Measurment where the difference between two degrees is meaningful
Ratio Variable
Has all the properties of interval plus a clear definition of 0.0
One-Tailed Test
Appropriate when a research hypothesis implies that an observed mean can onlybe greater than or less than a hypothesized value
Two-Tailed Test
Tests for differences from the population mean that are iether greater or less. Extrememe values of the normal curve on both the right and left are considered. When a reaserch qeustion does not specify whether a difference should be greater than or less than, a two tailed test is most appropriate
Chi Square Test
Tests for statistical significance. Is particularly appropriate for testing hypotheses about frequencies arranged in a frequency or contingency table
Goodness of Fit (GOF)
A general term representing how well some computed table or matrix of values matches some population or predetermined table or matrix of the same size. More often than not the test is between a table of observed frequency counts and another table of expected values (central tendancy) for those counts
Hypothesis Test of a proportion
Conceptually similar to the one used when the mean is the characteristic of interest but that differs in the mathematical formation of the standard error of the proportion