1. Variables and Data

2. 3. A car’s fuel efficiency
In statistics the term “variable” has a meaning that is different from its common usage in algebra or functions:
In statistics, a variable is an attribute or characteristic of an object/event/person that can be assessed or measured in some way across a group of comparable individual objects/events/persons possessing it
Examples:
1. A person’s hair color
2. A person’s height
3. A car’s fuel efficiency
4. A student’s GPA
Others?

3. 3. A car’s fuel efficiency
Examples:
1. A person’s hair color
2. A person’s height
3. A car’s fuel efficiency
4. A student’s GPA
Variable 1 is called a categorical variable, because the “values” it can assume are described by inclusion in a particular group or categories: e.g., fair, dark, red, blonde, etc
Variables 2-4 are called quantitative variables, because they can assume values that are numerical measurements (for which arithmetical operations make sense)

4. 3. A car’s fuel efficiency
Examples:
1. A person’s hair color
2. A person’s height
3. A car’s fuel efficiency
4. A student’s GPA
A subtle distinction
A Variable and its “values” are not one and the same thing: the particular values that an attribute assumes are called data—they are an expression of the state (categorical) or amount (quantitative) of the attribute and are not the same thing as the attribute per se
Examples:
Fair, dark, red, blonde are categories that describe particular states that the attribute “Hair color” can assume, but they don’t describe the attribute per se

5. Example: A data set lists apartments available for students to rent
Example: A data set lists apartments available for students to rent. Information provided includes the monthly rent, the number of bedrooms, whether or not cable is included free of charge, whether or not pets are allowed, and the distance to campus.
What constitutes the individuals or cases in the data set?
Identify the variables that the data set describes
Specify whether each variable is categorical or quantitative
How might we organize the data set for ease of comparison across all the cases on the same variables?

7. Consider the event “Murder”
What attributes of a murder might be of interest to identify and assess/measure across all murder cases?
List some such variables; specify whether each is categorical or quantitative

8. Case table for murders committed in Chicago in 1990