Let’s start from the types of data we can have.
There is categorical and numerical data.
Categorical data describes categories or groups.
One example is car brands like Mercedes, BMW and Audi – they show different categories.
Another instance is answers to yes and no questions.
If I ask questions like: Are you currently enrolled in a university?
Or, Do you own a car?
Yes and no would be the two groups of answers that can be obtained.
This is categorical data.
*** Numerical data, on the other hand, as its
name suggests, represents numbers.
It is further divided into two subsets: discrete and continuous.
Discrete data can usually be counted in a finite matter.
A good example would be the number of children that you want to have.
Even if you don’t know exactly how many, you are absolutely sure that the value will
be an integer such as 0, 1, 2, or even 10.
Another instance is grades on the SAT exam.
You may get 1000, 1560, 1570 or 2400.
What is important for a variable to be defined as discrete is that you can imagine each member
of the dataset.
Knowing that SAT scores range from 600 to 2400 and 10 points separate all possible scores
that can be obtained is key.
It’s easier to understand discrete data by saying it’s the opposite of continuous
data.
Continuous data is infinite and impossible to count.
For instance, your weight can take on every value in some range.
Let’s dig a bit deeper into this.
You get on the scale and the screen shows 150 pounds, or 68.0389 kilograms.
But this is just an approximation.
If you gain 0.01 pound, the figure on the scale is unlikely to change, but your new
weight will be 150.01 pounds or 68.0434 kilograms.
Now think about sweating.
Every drop of sweat reduces your weight by the weight of that drop, but once again, a
scale is unlikely to capture that change.
The process of losing and gaining weight occurs all the time.
Your exact weight is a continuous variable – it can take on an infinite amount of values
no matter how many digits there are after the dot.
To sum up, your weight can vary by incomprehensibly small amounts and is continuous, while the
number of children you want have is directly understandable and is discrete.
Just to make sure – here are some other examples of discrete and continuous data:
• Grades at university are discrete – A, B, C, D, E, F, or 0 to 100 percent.
• The number of objects in general.
No matter if bottles, glasses, tables, or cars.
They can only take integer values • Money can be considered both, but physical
money like banknotes and coins are definitely discrete.
You can’t pay $1.243.
You can only pay $1.24.
That’s because the difference between two sums of money can be 1 cent at most.
What else is continuous?
Apart from weight, other measurements are also continuous.
Examples are: • Height
• Area • Distance
• And time All of these can vary by infinitely smaller
amounts, incomprehensible for a human.
Time on a clock is discrete, but time in general isn’t!
It can be anything like 72.123456 seconds.
We are constrained in measuring weight, height, area, distance, and time by our technology,
but in general, they can take on any value.
Alright!
These were the types of data.