Types of Measurement Scale
Measurement is a process of assigning numbers/values to a physical condition, phenomenon, or status. There are four different scales of measurement. The data can be defined as being one of the four scales. The four types of scales are:
-
- Nominal scale
- Ordinal scale
- Interval scale
- Ratio scale
Nominal scale
- Example: Name, Board, Male, Female, Blood group, etc.
- A nominal scale consists of a set of categories that have different names.
- Nominal is naming categories without any order. You cannot put it in descending or ascending order.
- When the data for a variable consists of labels or names used to identify the characteristic of an observation, the scale of measurement is considered a nominal scale.
- Sometimes nominal variables might be numerically coded. For example, Men are coded as 1 and Women as 2.
-
- If we say – the temperature inside the room is comfortable – Then the temperature as a variable is nominal.
- If we say the outside Temperature is uncomfortable – Then the temperature as a variable is nominal.
-
Ordinal scale
- Example: Customer rating for services offered as excellent/good/poor.
- Ordinal – relating to the order of something in a series.
- The data obtained are the labels—excellent, good, or poor
-
- Individual data has properties of nominal data. Excellent is nominal data. But when put together as excellent/good/poor, it becomes ordinal data.
- Data can be ranked or ordered, with respect to the customer rating of service quality.
-
- An ordinal scale consists of a set of categories that are organized in an ordered sequence. Measurements on an ordinal scale rank observations in terms of size or magnitude.
- Data exhibits properties of nominal data and the order or rank of data is meaningful, the scale of measurement is considered an ordinal scale.
-
- If we say – the temperature inside the room is cold outside the temperature is warm and in the desert area temperature is hot – Then the temperature as a variable is ordinal.
-
Other Examples:
- Restaurants food rating
-
-
- Very good
- Good
- Not good
- Poor
-
-
- Performance of school students
-
-
- Ist
- IInd
- IIIrd
-
-
- Evaluating the mobile signal breakdown
-
-
- Very often
- Often
- Not often
- Not at all
-
-
- Survey question
-
-
- Totally agree
- Agree
- Neutral
- Disagree
- Totally disagree
-
-
Interval scale
- Example: Percentile, CGPA, Grade, Temperature in degrees Fahrenheit (200F), Temperature in degree centigrade (700C), pH value, SAT score, Specific gravity, etc.
- An interval scale consists of ordered categories that are all intervals of exactly the same size. Equal differences between numbers on the scale reflect equal differences in magnitude.
- A zero point on an interval scale is arbitrary and does not indicate a zero amount of the variable being measured.
-
- On the Temperature Celsius scale: zero degree (0oC) temperature is defined as the temperature of ice and water mixture in equilibrium at 1 atmosphere. Therefore 0oC is a reference point, not an absolute zero. Hence Celsius scale is an interval scale.
- On the Fahrenheit scale: Zero degree 0oF temperature is considered as the freezing temperature of brine. Therefore 0oF is a reference point, not an absolute zero. Hence Fahrenheit scale is an interval scale.
-
- Interval scale has Ordinal data properties + fixed interval value. Example: temp 20OC, 21OC, 220C….., the temp can be taken in an interval of 10C.
- The interval scale is quantitative as it can quantify the difference between the values. It allows calculating the mean and median of the variables
-
- If we say – the temperature inside the room is comfortable and the outside temperature is uncomfortable – Then the temperature as a variable is nominal.
- If we say – the temperature inside the room is cold outside the temperature is warm and in the desert area temperature is hot – Then the temperature as a variable is ordinal.
- If we say – the temperature inside the AC room is 22°C and the temperature outside the room is 45°C – Then the temperature as a variable is Interval.
-
Ratio scale
- Example: height, weight, age, marks, speed, distance, Temperature in Kevin, light intensity, etc.
- A ratio scale is an interval scale + with an absolute zero point.
- The ratio scale has an absolute zero
- It doesn’t have negative numbers, because of its zero-point feature.
-
- The temperature scale in Kelvin is a ratio scale variable because its zero value is absolute zero (0ok). 0o K is the lowest possible temperature.
-
- Ratio is a numerical value therefore it can be added, subtracted, multiplied, or divided
-
- If we say – the temperature inside the AC room is 22°C and the temperature outside the room is 45°C – Then the temperature as a variable is Interval.
- If we say – the temperature inside the AC room is 295°K (273+ 22) and the temperature outside the room is 318°K (273+45) – Then the temperature (measured on the Kelvin scale) as a variable is Ratio.
-
Comparison of Nominal scale, Ordinal scale, Interval scale, and Ratio scale:
- Refer comparison in the below table
Also Read
- https://matistics.com/statistics-data-variables/
- https://matistics.com/descriptive-statistics/
- https://matistics.com/1-1-measurement-scale/
- https://matistics.com/point-biserial-correlation-and-biserial-correlation/
- https://matistics.com/2-0-statistics-distributions/
- https://matistics.com/1-2-statistics-population-and-sample/
- https://matistics.com/7-hypothesis-testing/
- https://matistics.com/8-errors-in-hypothesis-testing/
- https://matistics.com/9-one-tailed-hypothesis-test/
- https://matistics.com/10-statistical-power/
- https://matistics.com/11-t-statistics/
- https://matistics.com/12-hypothesis-t-test-one-sample/
- https://matistics.com/13-hypothesis-t-test-2-sample/
- https://matistics.com/14-t-test-for-two-related-samples/
- https://matistics.com/15-analysis-of-variance-anova-independent-measures/
- https://matistics.com/16-anova-repeated-measures/
- https://matistics.com/17-two-factor-anova-independent-measures/
- https://matistics.com/18-correlation/
- https://matistics.com/19-regression/
- https://matistics.com/20-chi-square-statistic/
- https://matistics.com/21-binomial-test/