Types of Data

Types of Data

Overview of Data Types

  • The information is categorized into four primary types of data:

    • Nominal

    • Ordinal

    • Interval

    • Ratio

Nominal Data

  • Definition: The simplest form of data in which options are categorized or labeled. There are no intrinsic numeric values associated with these categories.

    • Example: Categories of race such as:

    • Black

    • Asian

    • White

    • American Indian

    • Native Hawaiian

  • Characteristics:

    • Non-numeric categories.

    • Cannot perform mathematical operations on nominal data.

Ordinal Data

  • Definition: Data that can be ranked or ordered. However, the intervals between the categories are not uniform, meaning that the distance from one option to the next is variable, preventing the application of most mathematical principles.

    • Example: Levels of confidence such as:

    • Very Confident

    • Somewhat Confident

    • Pretty Confident

    • A Little Confident

    • Not Confident at All

  • Characteristics:

    • Rankings exist, but the gaps between ranks are not consistent.

Interval Data

  • Definition: Data that is not only rank-ordered but also possesses equal intervals between each category, making it equidistant. However, interval data does not have an absolute zero.

    • Example: Temperature measurements in degrees such as:

    • 0 degrees

    • 10 degrees

    • 20 degrees

    • 30 degrees

    • -10 degrees

  • Characteristics:

    • Allows addition and subtraction operations.

    • Cannot meaningfully interpret ratios between values (e.g., 20 degrees is not twice as hot as 10 degrees).

Ratio Data

  • Definition: This type of data is similar to interval data but includes a true zero, which means that zero signifies the absence of the quantity being measured.

    • Example: Speed measurements in miles per hour (MPH) such as:

    • 0 MPH (indicates no speed)

    • 5 MPH

    • 10 MPH

    • 15 MPH

    • 20 MPH

  • Characteristics:

    • Allows all mathematical operations, including addition, subtraction, multiplication, and division.

    • Enables meaningful comparison of ratios (e.g., 20 MPH is twice as fast as 10 MPH).

    • The presence of a true zero makes it the most informative level of data analysis.

Summary of Data Types

  • Nominal: Categorizes options with no numeric value.

  • Ordinal: Ranks categories in order with variable intervals.

  • Interval: Ranks options that have equal, equidistant intervals but no true zero.

  • Ratio: Ranks options with equal intervals that include a true zero, allowing for all types of arithmetic operations.

Types of Statistical Analysis Applicable

  • Nominal: Requires non-parametric statistics.

  • Ordinal: Requires non-parametric statistics.

  • Interval: Can use parametric statistics.

  • Ratio: Can use parametric statistics.