MM - Discrete vs Continuous Data Lesson

Discrete vs Continuous Data

Data is generally categorized into 2 different types - discrete and continuous.  Discrete variables can only take on a limited number of values (e.g., only whole numbers and things that can be counted) while continuous variables can take on any value and any value between two values (e.g., fractions and decimal).  Discrete variables can also include data with distinct categories such as gender or ice cream flavor.

Graphical Representations

Now that you know what discrete and continuous data is, let's look at ways the data can be represented in graphs.

The above graph represents discrete data.  Between the years of 1800 and 2000, the population grew from approximately 1 million people to 7 million people.  Since the number of people can only be a whole number, it is discrete.  We will never have a portion of a person.  

 

This graph above also represents discrete data.  The more years the money is invested, the more money the account makes each year.  Money is discrete because we can count it.  It can be measured in millions of dollars, hundreds of dollars or even in smaller units such as cents.  We will never have any values between 1 cent and 2 cents.  

The above graph is continuous.  We can see that as the day progresses the glucose blood levels go up and down seemingly after meals.  We can see on the graphs that the units of measure for glucose blood levels is in mg/dL.  This is a quantity that can take on any value continuously.  We could have a blood glucose level of 3.5 mg/dL but then again we could also have 3.554678 mg/dL.  There are infinite numbers between 3.5 and 3.554678 that can measure blood glucose level, just as there are infinite values between the lowest glucose level and the highest glucose level.  

The above graph also displays continuous data.  We can see on the left side that we have the average monthly temperature in Celsius and Fahrenheit.  Temperature is continuous and a value that is measured, not counted.

Summary:

Discrete Data:  Data you can count and you cannot have portions of a whole.  Examples:  people, number of test questions, home runs

Continuous Data:  Data in which there are infinite values between one value and another.  Examples: measurements, time, temperature

Discrete vs Continuous Data Self-Assessment

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