1. Unit 1
Section 1.2

2. 1.2: Data Classification Variables can be classified in two ways:
Qualitative Variable– variables that can be placed into distinct categories, according to some characteristic or attribute.
Quantitative Variable– variables that are numerical and can be ordered or ranked.

3. Quantitative Variables
Section 1.2
Quantitative Variables
There are two types of quantitative variables:
Discrete Variables – can be assigned values such as 0, 1, 2, 3. Variables are able to be counted.
Continuous Variables – can assume an infinite number of values between any two specific values. Values are obtained by measuring (often include decimals and fractions).

4. The classification of variables can be summarized as follows:
Section 1.2
The classification of variables can be summarized as follows:
Data
Qualitative
Quantitative
Discrete
Continuous

5. Section 1.2 Measurement Scales
Nominal – classifies data using names, labels, or qualities.
Mutually exclusive (non-overlapping)
Exhausting categories (not infinite)
No order or ranking can be imposed on the data.
Lowest level of measurement.
Qualitative data only.
No mathematical computations can be made
Examples: eye color, political party, zip code, Social Security number

6. Section 1.2 Measurement Scales
Ordinal – classifies data into categories that can be ranked.
Precise differences between the ranks are not meaningful.
Second lowest level of measurement
Can be qualitative or quantitative.
Examples: letter grades, Olympic medals

7. Section 1.2 Measurement Scales
Interval – classifies data into categories that can be ranked and have precise differences (i.e. the difference between 10 and 20 means the same as between 30 and 40).
Zero represents a position on the scale, but does not necessarily imply “none.”
Second highest level of measurement.
Quantitative data only.
Examples: temperature (F and C)

8. Section 1.2 Measurement Scales
Ratio - possesses all the characteristics of interval measurement and there exists a true zero.
Highest level of measurement
Zero is an inherent zero (implies “none”)
A ratio of two data values can be formed.
Quantitative data only.
Examples: height, weight, time

9. Determine if one data value is a multiple of another
Section 1.2
Level of Measurement
Put data in categories
Arrange data in order
Subtract data values
Determine if one data value is a multiple of another
Nominal
Yes No
Ordinal
Interval
Ratio

10. Homework
Pg. 13 & 14: 1 – 31 ODD