Statistics Ch 1.2 Four Levels of Measurement

Nominal Data

A categorical data type that describes qualitative characteristics or groups with no inherent numerical value, order, or rank between categories.

The first level of measurement. The most basic level of measurement.

Ex: gender, ethnicity, blood type, personal preferences (fav color), etc.

Often used in surveys for demographics.

Ordinal Data

A categorical data type that describes categories with a meaningful order or rank difference between the options. Each option has a different value UNLIKE nominal.

The second level of measurement.

Ex: income levels(high, middle low)

levels of agreement(agree,neutral, disagree) levels of satisfaction(poor, average, high)

Interval Data

A numerical data type that has an order and equal spaces between measurement points, but the zero point is arbitrary. Equal spaces between points(UNLIKE ordinal data).

The third level of measurement.

Ex: credit scores (300-850)

GMAT scores (200-800)'

Temperature Farenheit ( zero DOES NOT mean NOTHING)

zero point is ARBITRARY. cant get a zero credit score, or gmat score.

CONTINUOUS data type

Ratio Data

The most sophisticated level of measurement that has an order, equal spaces between points, and a meaningful absolute zero point.

The fourth level of measurement of data.

Ex: weight, height, length, time,

Kelvin

zero point means NOTHING. zero point is NOT arbritrary.

CONTINUOUS data type

Categorical/qualitative Data

Data that reflect qualitative characteristics or categories, which can be nominal or ordinal in nature.

Using this type of data includes assigning numbers to data to sort the data.

Ex: Female can be assigned 1, Male assigned 2

Ex: Gender, hair color, ethnicity

Numerical Data/ Scale Data

Data that are inherently numbers-based and quantitative, which can be interval or ratio in nature. Naturally measured as numbers.

Ex: Age, weight, height

Levels of Measurement

The classification of data types that impacts which statistical tests can be used on them.

Statistical Tests

Procedures that can be applied to data sets, which depend on the level of measurement of the data.

Zero Point

The reference point in measurement; in interval data, it is arbitrary, while in ratio data, it is meaningful.

Continuous Data

Data types (interval and ratio) that can take on any value within a range, as opposed to discrete data.

Scale Data

A term used in SPSS to refer to numerical data, encompassing both interval and ratio levels of measurement.

ratio and interval

What two levels of data measurement are CONTINUOUS?

nominal and ordinal

What two levels of data measurement are NOT continuous?