Nominal, Ordinal, Interval & Ratio Variable + Examples

A nominal variable is a type of variable that is used to name, label, or categorize particular attributes that are being measured. It takes qualitative values representing different categories, and there is no intrinsic ordering of these categories. The scale of measurements in analyzing data is essential as using the correct scale ensures that you conduct the right statistical tests and get a valid result. On the other hand, a wrong scale can cause flawed analysis which can affect the credibility of your results. Ratio variables sit alongside nominal, ordinal, and interval variables in the categorization of variables.

If you work on your computer eight hours six days a week, your MacBook is likely the cheapest thing you own. These represent scenarios where we would classify time as a ratio variable instead of an interval variable. One recipe has a total cooking time of 40 minutes and the other has a cooking time of 20 minutes. Unlike ordinal variables that take values with no standardized scale, every point in the interval scale is equidistant. Arithmetic operations can also be performed on the numerical values of the interval variable.

It takes six hours and 12.5 minutes for the water at the shore to go from high to low, or from low to high. Reading this article, you’ll understand why the price/time ratio works and how you can use it to make better expenditure choices. Get instant access to video lessons taught by experienced investment bankers. Learn financial statement modeling, DCF, M&A, LBO, Comps and Excel shortcuts.

Especially for mathematics tests, or word problems we see many examples of ratio variables. Similar to the nominal variable, there is no standard classification of ordinal variables into types. However, we will be classifying them according to the value assignment. Ordinal Variable type based on numerical and non numerical values. An ordinal variable is a type of measurement variable that takes values with an order or rank. It is the 2nd level of measurement and is an extension of the nominal variable.

To calculate the times interest earned ratio, we simply take the operating income and divide it by the interest expense. The resulting ratio shows the number of times that a company could pay off its interest expense using its operating income. Conceptually identical to the interest coverage ratio, the TIE ratio formula consists of dividing the company’s EBIT by the total interest expense on all debt securities. As a rule, companies that generate consistent annual earnings are likely to carry more debt as a percentage of total capitalization. When it comes to data analysis and statistics, understanding the different measurement scales is crucial. While they share some similarities, they also have distinct attributes that set them apart.

Generating enough cash flow to continue to invest in the business is better than merely having enough money to stave off bankruptcy. As a rule of thumb, everything that costs more than 0.01$/minute has an unfavorable price per life minute. Note, even though a variable may discrete, if the variable takes on enough different values, it is often treated as continuous.

The gap between a score of 20 and 30 is identical to that between 30 and 40. However, a score of 0 does not mean the total lack of is time an interval or ratio variable explanation and example knowledge or aptitude. Elevations Above Sea LevelThe measure of elevations above sea level serves as an interval variable.

Ordinal

There are occasions when you will have some control over the measurement scale. For example, with temperature, you can choose degrees C or F and have an interval scale or choose degrees Kelvin and have a ratio scale. With income level, instead of offering categories and having an ordinal scale, you can try to get the actual income and have a ratio scale. Generally speaking, you want to strive to have a scale towards the ratio end as opposed to the nominal end. A ratio scale, on the other hand, possesses all the properties of a nominal, ordinal, and interval scale, with the additional feature of a true zero point.

Definition of Ratio Data

When working with ratio variables, but not interval variables, the ratio of two measurements has a meaningful interpretation. For example, because weight is a ratio variable, a weight of 4 grams is twice as heavy as a weight of 2 grams. However, a temperature of 10 degrees C should not be considered twice as hot as 5 degrees C. If it were, a conflict would be created because 10 degrees C is 50 degrees F and 5 degrees C is 41 degrees F. Another example, a pH of 3 is not twice as acidic as a pH of 6, because pH is not a ratio variable.

Ordinal Variable With Numeric Value

For instance, if someone weighs 60 kilograms and another person weighs 30 kilograms, we can confidently say that the former weighs twice as much as the latter. TIE is calculated as EBIT (earnings before interest and taxes) divided by total interest expense. The higher the times interest earned ratio, the more likely the company can pay interest on its debts. Times interest earned ratio measures a company’s ability to continue to service its debt.

Characteristics of Nominal Variable

When the variable equals 0.0, there is none of that variable. The scale has equal intervals, but a pH of 0 does not signify the absence of acidity or alkalinity. Decibel LevelsDecibel levels follow an interval variable scale. A consistent interval exists between units of measurement, but zero decibels does not indicate the absence of sound. Test ScoresScores on academic tests form an interval variable.

It helps to determine the kind of data to be collected, how to collect it and which method of analysis should be used. Also, all statistical analysis including mean, mode, median, etc. can be calculated on the ratio scale. There are also 2 main categories of ordinal variables, namely; the matched and unmatched category. The most common way that nominal scale data is collected is through a survey. For example, a researcher might survey 100 people and ask each of them what type of place they live in. Most quantitative data is ratio data because it uses a true zero scale.

Times Interest Earned Ratio (TIE)

Zero distance signifies that there’s no separation between two points.
For example, we can calculate that the temperature increased by 2 degrees Celsius from Monday to Tuesday and decreased by 7 degrees Celsius from Wednesday to Thursday.
For instance, if someone weighs 60 kilograms and another person weighs 30 kilograms, we can confidently say that the former weighs twice as much as the latter.
The purpose of the TIE ratio, also known as the interest coverage ratio (ICR), is to evaluate whether a business can pay the interest expense on its debt obligations in the next year.

How we measure variables is called scale of measurements, and it affects the type of analytical techniques that can be used on the data, and conclusions that can be drawn from it. Measurement variables are categorized into four types, namely; nominal, ordinal, interval, and ratio variables. An example of interval data is temperature measured in degrees Celsius or Fahrenheit. Let’s consider the temperature in degrees Celsius as our example. In this case, the numerical values represent the magnitude of the variable (temperature) on a numerical scale.

Importance of Times Interest Earned Ratio

The debt service coverage ratio (DSCR) is net operating income divided by debt service, which includes principal and interest.
So it’s safe to say that the scale of measurement of data matters under certain conditions like the following.
For example, an organization who wants to receive feedback from its customers may ask, “How do you think we can improve our service?
The times interest earned (TIE) ratio is a measure of a company’s ability to meet its debt obligations based on its current income.
The interval variable is a measurement variable that is used to define values measured along a scale, with each point placed at an equal distance from one another.

And while this holds true, it’s how they spend their money that can make all the difference. We could also say that one recipe has a cooking time that is twice as long as the other. Making great buying decisions doesn’t need to feel complex or exhausting. Remembering to divide the price by the time you’ll use it can actually be quite fun.

Suppose we keep track of how long it takes people to run a marathon. The key distinction between interval and ratio data is the presence of a meaningful zero point. In ratio data, zero indicates a complete absence, while in interval data, zero is an arbitrary reference point.