scales of measurement
DESCRIPTION
Scales of Measurement. Nominal classification labels mutually exclusive exhaustive different in kind, not degree. Scales of Measurement. Ordinal rank ordering numbers reflect “greater than” only intraindividual hierarchies NOT interindividual comparisons. - PowerPoint PPT PresentationTRANSCRIPT
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Scales of MeasurementScales of Measurement
Nominalclassification
labels
mutually exclusive
exhaustive
different in kind, not degree
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Scales of MeasurementScales of Measurement
Ordinalrank ordering
numbers reflect “greater than”
only intraindividual hierarchies
NOT interindividual comparisons
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Scales of MeasurementScales of Measurement
Intervalequal units on scale
scale is arbitrary
no 0 point
meaningful differences between scores
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Scales of MeasurementScales of Measurement
Ratiotrue 0 can be determined
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Contributions of each scaleContributions of each scale
Nominal creates the group
Ordinal creates rank (place) in group
Interval relative place in group
Ratio comparative relationship
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Graphing dataGraphing data
X Axis
horizontal
abscissa
independent variable
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Y Axis
vertical
ordinate
dependent variable
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Types of GraphsTypes of Graphs Bar graph
qualitative or quantitative data
nominal or ordinal scales
categories on x axis, frequencies on y
discrete variables
not continuous
not joined
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Bar GraphBar Graph
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Types of GraphsTypes of Graphs
Histogram
quantitative data
continuous (interval or ratio) scales
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HistogramHistogram
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Types of GraphsTypes of Graphs
Frequency polygon
quantitative data
continuous scales
based on histogram data
use midpoint of range for interval
lines joined
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Frequency PolygonFrequency Polygon
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Interpreting ScoresInterpreting Scores
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Measures of Central TendencyMeasures of Central Tendency
Mean Median Mode
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Measures of VariabilityMeasures of Variability
Range Standard Deviation
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Effect of standard deviationEffect of standard deviation
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Assumptions of Normal Distribution
(Gaussian)
Assumptions of Normal Distribution
(Gaussian)
The underlying variable is continuous The range of values is unbounded The distribution is symmetrical The distribution is unimodal May be defined entirely by the mean and
standard deviation
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Normal DistributionNormal Distribution
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Terms of distributionsTerms of distributions
Kurtosis Modal Skewedness
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Skewed distributionsSkewed distributions
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Linear transformationsLinear transformations
Expresses raw score in different units takes into account more information allows comparisons between tests
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Linear transformationsLinear transformations
Standard Deviations + or - 1 to 3 z score 0 = mean, - 1 sd = -1 z, 1 sd = 1 z T scores
removes negatives removes fractions 0 z = 50 T
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ExampleExample
T = (z x 10) + 50
If z = 1.3
T = (1.3 x 10) +50
= 63
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ExampleExample
T = (z x 10) + 50
If z = -1.9
T = (-1.9 x 10) +50
= 31
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Linear TransformationsLinear Transformations
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Examples of linear transformationsExamples of linear transformations
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Chapter 3 - assignmentChapter 3 - assignment
Which scale is used for your measure? Is it appropriate? Are there alternates?
How will you graph the data from your measure?
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