 # What Are The Six Different Types Of Continuous Data?

## What are the 4 types of data?

In statistics, there are four data measurement scales: nominal, ordinal, interval and ratio.

These are simply ways to sub-categorize different types of data (here’s an overview of statistical data types) ..

## What is the continuous data?

Discrete data is information that can only take certain values. Continuous data is data that can take any value. … Height, weight, temperature and length are all examples of continuous data.

## What type of data is eye Colour?

Expert Answers info In other words, when you look at things where there is a first, a second, a third and so on, you have ordinal data. But eye color is not this kind of data. Blue eyes do not come before brown eyes or vice versa. Therefore, eye color is not an example of ordinal data.

## What are examples of continuous variables?

Continuous variables can take on almost any numeric value and can be meaningfully divided into smaller increments, including fractional and decimal values. You often measure a continuous variable on a scale. For example, when you measure height, weight, and temperature, you have continuous data.

## What are the 2 types of data?

Understanding Qualitative, Quantitative, Attribute, Discrete, and Continuous Data TypesAt the highest level, two kinds of data exist: quantitative and qualitative.There are two types of quantitative data, which is also referred to as numeric data: continuous and discrete.More items…•

## What is the difference between a discrete and continuous variable?

“A discrete variable is one that can take on finitely many, or countably infinitely many values”, whereas a continuous random variable is one that is not discrete, i.e. “can take on uncountably infinitely many values”, such as a spectrum of real numbers.

## Is Money discrete or continuous?

A continuous distribution should have an infinite number of values between \$0.00 and \$0.01. Money does not have this property – there is always an indivisible unit of smallest currency. And as such, money is a discrete quantity.

## What type of data is income?

The difference between interval and ratio data is simple. Ratio data has a defined zero point. Income, height, weight, annual sales, market share, product defect rates, time to repurchase, unemployment rate, and crime rate are examples of ratio data.

## What type of data is gender?

For example, gender is a categorical data because it can be categorized into male and female according to some unique qualities possessed by each gender. There are 2 main types of categorical data, namely; nominal data and ordinal data.

## Is age an example of continuous data?

A variable is said to be continuous if it can assume an infinite number of real values. Examples of a continuous variable are distance, age and temperature. … For example, the height of a student is a continuous variable because a student may be 1.6321748755…

## What kind of variable is age?

Mondal suggests that age can be viewed as a discrete variable because it is commonly expressed as an integer in units of years with no decimal to indicate days and presumably, hours, minutes, and seconds.

## Is age continuous or categorical?

Continuous variables are measured numerically, and have an infinite number of possible values. For example, an age variable measured continuously could have a value of 23.487 years old—if you wanted to get that specific!

## What type of data is age?

Age is frequently collected as ratio data, but can also be collected as ordinal data. This happens on surveys when they ask, “What age group do you fall in?” There, you wouldn’t have data on your respondent’s individual ages – you’d only know how many were between 18-24, 25-34, etc.

## What are the types of continuous data?

Familiar types of continuous variables are income, temperature, height, weight, and distance. There are two main types of continuous variables: interval and ratio.

## What are examples of discrete and continuous variables?

For example, you could be: 25 years, 10 months, 2 days, 5 hours, 4 seconds, 4 milliseconds, 8 nanoseconds, 99 picosends…and so on. Time is a continuous variable. You could turn age into a discrete variable and then you could count it.