Presentation on theme: "Variables and Data. In statistics the term variable has a meaning that is different from its common usage in algebra or functions: In statistics, a variable."— Presentation transcript:
Variables and Data
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 persons hair color 2. A persons height 3. A cars fuel efficiency 4. A students GPA Others?
Examples: 1. A persons hair color 2. A persons height 3. A cars fuel efficiency 4. A students 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)
Examples: 1. A persons hair color 2. A persons height 3. A cars fuel efficiency 4. A students 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 datathey 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 dont describe the attribute per se
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?
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
Case table for murders committed in Chicago in 1990