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.
Examples: eye color, political party, zip code

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.
There is no meaningful zero (the number zero represents a position on the scale).
Second highest level of measurement
Examples: temperature, money in a savings account

8. Section 1.2 Measurement Scales
Ratio - possesses all the characteristics of interval measurement and there exists a true zero.
Highest level of measurement
Examples: height, weight, time

9. Homework Page 13: Nominal, Ordinal Ordinal, Interval, Ratio
False: Data at the ordinal level can be qualitative or quantitative.
False: For data at the ordinal level, you cannot calculate meaningful differences between data entries.
False: Less types of calculations can be performed with data at the nominal level than with data at the interval level.
False: Data at the ratio level can be put in order.

10. Homework
Pg 13: 7 – 31 ODD