Data Classification
DATA classification
 Qualitative Data: consists of attributes, labels, or
nonnumerical entries.
 Examples: red, Mr. Smith, Dogs
 Quantitative Data: consists of numerical
measurements or counts.
 Examples: 5.5 inches, 10, $23,290
Qualitative VS Quantitative
 Telephone number
 Qualitative
 Length of a song
 Quantitative
 Responses in an opinion poll
 Qualitative
Inherent zero
 An inherent zero represents the position on the
number line.
 Not an inherent zero implies that there are none.
4 levels of Measurement
 Nominal




Are Qualitative only
Can be categorized by names, labels, or qualities
Can’t do mathematical calculations
Example: Colors, Music
 Ordinal
 Are Qualitative and Quantitative
 Can be put in order or ranked, but difference between them
are meaningless.
 Examples: Top 5 teachers, movies
4 levels of Measurement
 Interval
 Can be ordered and you can calculate meaningful differences.
 Zero is not an inherent zero.
 Examples: 1999, 2001, 2004, 2008, 2009, 2010
Temperature
 Ratio




Is similar to interval but 0 is an inherent zero.
Find ratios of values
Can’t go below zero.
Examples: Red Sox: 128 homeruns, Pirates: 78 homeruns
Precipitation
Examples
 Body temperature in Fahrenheit of a swimmer
 interval
 Collection of phone numbers
 nominal
 Final standings for football Northeaster Conference
 ordinal
 Heart rate (beats per minute) of an athlete.
 Ratio
Chart
Levels of Measurement
Put data
in categories
Arrange data
in order
Subtract data
values
Nominal
Ordinal
Interval
Ratio
Yes
Yes
Yes
Yes
No
yes
yes
Yes
No
No
Yes
Yes
Homework: pg 15: 8- 24 Even
Determine if one
data valuse is a
multiple of another
No
No
No
Yes