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Statistics
is the branch of mathematics that analyzes and interprets data.

Data
are pieces of information, usually organized and expressed as numbers.

Measurement (Meline, pg. 70)
“the process of systematically assigning numbers to objects, persons or events according to some prescribed rules”

Steven’s classic levels
– ad become more rigorous, mathematically sound, ascending order
A. Nominal level of measurement
B. Ordinal level of measurement
C. Interval level of measurement
D. Ratio level of measurement

Steven’s classic levels
These levels “allow progressively more sophisticated quantitative procedures to be performed”
the statistics used to analyze the data depend on the scale of the data.

Nominal (“in name only”)
  Indicates a difference (category)
  In research, attributes often coded as a number (0, 1) but these are placeholders.
Examples: telephone numbers (has no quantitative value, not poorer if you have a 213 vs a 310 number, there is no quantitative operation)

Ordinal
 Indicates a difference (category)
  Indicates direction of difference, meaning,
  can be put into an order (rank)
  there is order, a direction of difference
 Differences between ranks not equal units (#1 rank would have more points)
Example: class rank  rating scale  Likert scaling (15 ranking)
 ** for both ordinal and nominal need statistics that will tell you
 a difference

Interval
  Indicates a difference (category)
  Indicates direction of difference
  Indicates amount of difference, in equal intervals
  (the difference between rank position is equal)
  No true zero in units of measure
  (usually an arbitraty number assigned)
Examples: temperature (Fahrenheit)
intelligence (IQ)

