In Statistics, the variables or numbers are defined and categorised using different scales of measurements. Each level of measurement scale has specific properties that determine the various use of statistical analysis. In this article, we will learn four types of scales such as nominal, ordinal, interval and ratio scale.
What is the Scale?
A scale is a device or an object used to measure or quantify any event or another object.
- Scale Factor Definition
- Measurement Of Objects
- Data Handling
- Sampling Methods
Levels of Measurements
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
A nominal scale is the 1st level of measurement scale in which the numbers serve as “tags” or “labels” to classify or identify the objects. A nominal scale usually deals with the non-numeric variables or the numbers that do not have any value.
Characteristics of Nominal Scale
- A nominal scale variable is classified into two or more categories. In this measurement mechanism, the answer should fall into either of the classes.
- It is qualitative. The numbers are used here to identify the objects.
- The numbers don’t define the object characteristics. The only permissible aspect of numbers in the nominal scale is “counting.”
Example:
An example of a nominal scale measurement is given below:
What is your gender?
M- Male
F- Female
Here, the variables are used as tags, and the answer to this question should be either M or F.
Ordinal Scale
The ordinal scale is the 2nd level of measurement that reports the ordering and ranking of data without establishing the degree of variation between them. Ordinal represents the “order.” Ordinal data is known as qualitative data or categorical data. It can be grouped, named and also ranked.
Characteristics of the Ordinal Scale
- The ordinal scale shows the relative ranking of the variables
- It identifies and describes the magnitude of a variable
- Along with the information provided by the nominal scale, ordinal scales give the rankings of those variables
- The interval properties are not known
- The surveyors can quickly analyse the degree of agreement concerning the identified order of variables
Example:
- Ranking of school students – 1st, 2nd, 3rd, etc.
- Ratings in restaurants
- Evaluating the frequency of occurrences
- Very often
- Often
- Not often
- Not at all
- Assessing the degree of agreement
- Totally agree
- Agree
- Neutral
- Disagree
- Totally disagree
Interval Scale
The interval scale is the 3rd level of measurement scale. It is defined as a quantitative measurement scale in which the difference between the two variables is meaningful. In other words, the variables are measured in an exact manner, not as in a relative way in which the presence of zero is arbitrary.
Characteristics of Interval Scale:
- The interval scale is quantitative as it can quantify the difference between the values
- It allows calculating the mean and median of the variables
- To understand the difference between the variables, you can subtract the values between the variables
- The interval scale is the preferred scale in Statistics as it helps to assign any numerical values to arbitrary assessment such as feelings, calendar types, etc.
Example:
- Likert Scale
- Net Promoter Score (NPS)
- Bipolar Matrix Table
Ratio Scale
The ratio scale is the 4th level of measurement scale, which is quantitative. It is a type of variable measurement scale. It allows researchers to compare the differences or intervals. The ratio scale has a unique feature. It possesses the character of the origin or zero points.
Characteristics of Ratio Scale:
- Ratio scale has a feature of absolute zero
- It doesn’t have negative numbers, because of its zero-point feature
- It affords unique opportunities for statistical analysis. The variables can be orderly added, subtracted, multiplied, divided. Mean, median, and mode can be calculated using the ratio scale.
- Ratio scale has unique and useful properties. One such feature is that it allows unit conversions like kilogram – calories, gram – calories, etc.
Example:
An example of a ratio scale is:
What is your weight in Kgs?
- Less than 55 kgs
- 55 – 75 kgs
- 76 – 85 kgs
- 86 – 95 kgs
- More than 95 kgs
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FAQs
Nominal: the data can only be categorized. Ordinal: the data can be categorized and ranked. Interval: the data can be categorized, ranked, and evenly spaced. Ratio: the data can be categorized, ranked, evenly spaced, and has a natural zero.
What are the 4 types of measurement scales? ›
Scales of measurement is how variables are defined and categorised. Psychologist Stanley Stevens developed the four common scales of measurement: nominal, ordinal, interval and ratio.
What are the 4 levels of measurement? ›
Statisticians often refer to the "levels of measurement" of a variable, a measure, or a scale to distinguish between measured variables that have different properties. There are four basic levels: nominal, ordinal, interval, and ratio.
How do interval and ratio scales compare use examples to clarify your answer? ›
The difference between interval vs ratio scale comes from their ability to dip below zero. Interval scales hold no true zero and can represent values below zero. For example, you can measure temperatures below 0 degrees Celsius, such as -10 degrees. Ratio variables, on the other hand, never fall below zero.
What is an example of interval and ratio data? ›
Examples of interval level data include temperature and year. Examples of ratio level data include distance and area (e.g., acreage).
What are nominal and ordinal examples? ›
Ordinal data is data that can be ranked or ordered. Examples include data taken from a poll or survey. Nominal data is data that can be made to fit various categories. Examples include whether an animal is a mammal, fish, reptile, amphibian, or bird.
What is an example of an ordinal scale? ›
Ordinal Scale Examples
Status at the workplace, tournament team rankings, order of product quality, and order of agreement or satisfaction are some of the most common examples of the ordinal Scale.
What is an example of an interval scale and a ratio scale? ›
Interval scale vs ratio scale: characteristics
| CHARACTERISTICS | INTERVAL SCALE | RATIO SCALE |
|---|
| Meaningful ratios | Ratios are not meaningful due to the lack of zero. | Ratios are meaningful due to the presence of zero. |
| Examples | IQ scores, celsius temperature, NPS data, etc. | Height, weight, income, etc. |
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An interval scale is one where there is order and the difference between two values is meaningful. Examples of interval variables include: temperature (Farenheit), temperature (Celcius), pH, SAT score (200-800), credit score (300-850).
Is age interval or ratio? ›
The short answer: Age is considered a ratio variable because it has a “true zero” value. It's possible for an individual to be zero years old (a newborn) and we can say that the difference between 0 years and 10 years is the same as the difference between 10 years and 20 years.
Depending on the question, age can be a nominal or ordinal variable. If the question is "How old are you?" it's a nominal variable. If the question is "What age range are you in?" it's an ordinal variable.
What are 4 levels of measurement with examples in PDF? ›
The most popular typology, developed by Stevens (1946), identifies four levels of measurement: nominal, ordinal, interval, and ratio. Each level identifies a different relationship between values and the appropriate corresponding descriptive and inferential statistics one may use.
Does ratio have a true zero? ›
A ratio scale is a quantitative scale where there is a true zero and equal intervals between neighboring points. Unlike on an interval scale, a zero on a ratio scale means there is a total absence of the variable you are measuring. Length, area, and population are examples of ratio scales.
Why is the ratio scale most powerful? ›
It's the highest ranked in the four levels of measurement, based on the precision involved. Ratio scales allow you to categorize and rank your data along equal intervals. The scale has a true zero and no negative values, allowing researchers to discover and describe the amount of magnitude involved.
Is temperature nominal or ordinal? ›
This means that temperature is ordinal data because it can be expressed in a given order such as extremely hot, very hot, hot, moderately hot, a little bit hot and so on. For example temperature between 20 and 30 degree Celsius can be considered hot.
What are the types of measurement scales? ›
Each of the four scales (i.e., nominal, ordinal, interval, and ratio) provides a different type of information.
What are the levels of measurement in data? ›
A variable has one of four different levels of measurement: Nominal, Ordinal, Interval, or Ratio. (Interval and Ratio variables are sometimes called Continuous or Scale).
What are scales of measurement ordinal? ›
The ordinal scale is the 2nd level of measurement that reports the ordering and ranking of data without establishing the degree of variation between them. Ordinal represents the “order.” Ordinal data is known as qualitative data or categorical data. It can be grouped, named and also ranked.
