Discrete And Continuous Data Defined

When dealing with data, one of the things we should take note of is the type of the data. Is it numeric or string? Boolean? Date, even?

If the data is numeric, we would then have to consider whether the data in a dataset is discrete or continuous. It is only after such a classification, that an analyst would be able to decide on the best way to visualize this data.

Discrete data

Data is said to be discrete if there the data points are distinct and separate from other data points in the dataset. There are restrictions to the value that these data points can have. Usually, these restrictions take the form of the value being a whole number and not a fraction.

Take for example the number of silver cars in a showroom, the number of people attending a Rolling Stones concert, or the number of eggs sold in a supermart on weekends. You can't have a fraction of a car, or a person. And definitely not half an egg, at least, in raw form.

Number of silver cars in
a showroom.

Think of discrete values as countable data. Numbers that have to be counted.

Discrete data is easy to visualize. Bar charts, line charts, etc, all these handle discrete data quite readily.

Continuous data

Data is said to be continuous if the values of data points can take on any value within a certain range. This usually means that the data can be from an infinitely precise measurement.

Take for example the temperatures taken on a certain day of the week, the speed of the cars on the road, or the heights of different buildings on a street. The values are not restricted to whole numbers - a temperature can be a value like 30.01657 degrees Celcius, for instance. Depending on how precise you wish to be, the figure could go on even longer.

Measurable values.

Think of continuous data as measurable values. Values that have to be measured by an instrument such as a thermometer or gauge.

Continuous data is best represented by line charts. If grouped into discrete categories of ranges, they can also be represented much the same as discrete data.

What about monetary figures, such as profits?

One might be tempted to think of this as a continuous measure, because profits is a measure of money, which uses decimals. For example, the figure 1,400,450.25. However, the decimals are actually representations of cents. So in essence, the figure means 140,045,025 cents. It's not a fraction, exactly.

Money can be counted.

Also, remember, discrete figures are counted. Money is counted. Therefore, monetary figures are discrete.

In a nutshell

The difference between discrete and continuous data is straightforward in most cases. It is usually when decimal places are involved, where confusion sets in.

See you lata, alli-data!
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