Types of Quantitative Variables and Data Classification

Quantitative Variable Classifications

• Discrete Quantitative Variables

  • Apply to values representing counts.

  • Must be whole numbers; results cannot contain a decimal.

  • Commonly identified by the phrase "the number of."

• Continuous Quantitative Variables

  • Apply to values representing measurements.

  • Results may contain decimals.

Determining Variable Type

• Step 1: Determine if results are numbers.

  • If no, the variable is Categorical.

  • If yes, proceed to the next question. Note that some numbers (e.g., Social Security Number, Driver's License Number, Employee ID) function as labels and are Categorical.

• Step 2: Determine if values are counts or measurements.

  • If the values represent counts or measurements, the variable is Quantitative.

  • Otherwise, it is Categorical.

Variable Examples and Classifications

• Number of Absences: Discrete Quantitative (count).

• Salary: Continuous Quantitative (measurement).

• Commute Time (in hours): Continuous Quantitative (measurement).

• Number of Promotions: Discrete Quantitative (count).

• Classification / Residence Type: Categorical.

• Number of Classes Fall 2022: Discrete Quantitative.

Introduction to Data Representation

• Methodology Selection: The type of tables and graphs used depends on the specific variable type (Quantitative vs. Categorical) and the nature of the data.

• Contingency Table Components:

  • Joint counts: Provides the total for specific characteristic intersections.

  • Row totals: Sum of all values within a specific row.

  • Overall Total: The sum total of all frequencies in the dataset.