Skip to main content
It looks like you're using Internet Explorer 11 or older. This website works best with modern browsers such as the latest versions of Chrome, Firefox, Safari, and Edge. If you continue with this browser, you may see unexpected results.

Data Vizualization (Showcase Workshop)

Quantitative Data

> Quantitative data can be:

  • counted
  • measured

It's ... NUMERICAL!

 

> Examples of quantitative data include:

  • the weight of VW buses
  • the wingspan of eagles
  • the number of cars passing through an intersection each hour

> What's CONTINUOUS quantitative data?

  • there's an infinite number of possible values for each outcome
  • when you take measurements, it's usually continuous data you're finding!

But...but...

  • You're right! - that doesn't mean the range of values you'd measure would be infinite.

 

> Examples of CONTINUOUS quantitative data include:

  • the surface water temperature of the Lincoln Park swimming pool (64.1, 62.8, 63.5, 65.0 ºF)
  • the hopping height of your pet jackrabbit (1.86, 2.41, 2.09, 2.11 m)
  • the weight of CMU football players

 

> So while there's likely an upper limit to the weight of a CMU football player...there's an infinite # of exact hopping heights that could be measured.

> What's DISCRETE quantitative data?

  • data with a limited # of possible outcome values
  • when you are counting sometime to collect data, it's often discrete!

 

> Examples of DISCRETE quantitative data include... 

  • # of passengers in a car
  • # of phone calls an office receives each day
  • # of puppies in a litter
  • # of credit hours registered for per student per semester

> Interval

  • Intervals between values are known
  • Intervals between values are equal
  • Example: temperature
    • Interval from 50°F to 60°F is known
    • Interval from 50°F to 60°F and 80°F to 90°F is equal
  • Where might I see INTERVAL data: usually within data collected in environmental science

 

> Ratio

  • A special case of INTERVAL data
  • Interval data that starts at 0
  • Where will I see RATIO data: environmental science - experimental research
    • Example: rainfall
      • starts at 0 inches (can't have negative rainfall!)
      • difference between 2 and 4 inches is known
      • difference between 2 and 4 inches = difference between 10 and 12 inches
    • Example: whale mass
      • starts at 0 (though no whale will weigh 0, they couldn't weigh LESS than 0!)

 

> Ordinal 

  • data has a relevant order
  • magnitude between values is unknown or unequal
  • When will I see ORDINAL data: survey data with ranked responses
  • Example: a satisfaction scale
    • scale from 1 to 5 (with 5 as highest satisfaction)
      • 5 = better than 3
      • 4 = better than 2
      • difference between 5 & 3? unknown
      • difference between 4 & 2? unknown
    • There's an order but the interval differences aren't necessarily meaningful

Where'd You Find this Good Info?