How much’, ‘How many’, ‘What percentage

What is Quantitative Data?
Quantitative data refers to data that can be expressed in numerical terms. Answers to questions like ‘How much’, ‘How many’, ‘What percentage’, and ‘How often’ are what constitutes quantitative data. Such data cannot be used for statistical analysis. However, you must try and identify relevant groups and descriptions to make sense of the data.
Quantitative Data Types with Examples
There are two main types of quantitative data. They are:
Discrete

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  Continuous
  

In simple terms, Discrete data is countable and Continuous data is measurable. Let’s explore the two types of data in detail.
Discrete data is data that can be expressed in specific values. These values are typically counted in whole numbers and cannot be broken down into smaller units. Discrete data is also known as attribute data. Thus, you can easily identify discrete quantitative data by questioning whether the given data can be counted or not. This type of data is usually represented using tally charts, bar charts, and pie charts.
A few examples of discrete data include:
Number of members in a team

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  Number of toffees in a packet
  
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  Number of questions in a test paper
  
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  Monthly profit of a business
  
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  Shoe size number
  

On the other hand, continuous data is data that can take any value. This value has a tendency to fluctuate over time. Thus, the value will vary over a given period of time, depending on when you seek the data. This type of quantitative data is usually represented using a line graph as a line graph aptly illustrates the data changes occurring over a period of time.
Continuous data can be further divided into two types, namely, ratio data and interval data. Statistically, the geometric or harmonic mean is calculated in ratio data while the arithmetic mean is calculated in interval data.
A few examples of continuous data include:

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  The daily temperature of a place
  
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  Height of a baby
  
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  Weight of a child
  
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  Wind speed
  
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  Length of a leaf