One vs Two Variable Data
What is a variable?
A characteristic that can change or vary between participants/records.
One Variable / Single Variable Data
A dataset or a single column from a dataset where each item has only one characteristic (variable) being measured or observed.
Marcus Doyle
198
118
4.78
33
DeShawn Rivers
185
93
4.41
37
Blake Armstrong
191
102
4.54
35
Jamal Carter
178
88
4.29
39
Trevor McKnight
195
109
4.65
32
Andre Lopez
183
96
4.50
36
Colton Hayes
200
124
4.89
31
Malik Jefferson
188
98
4.42
38
Jared Cole
180
85
4.31
40
Ethan Brooks
193
105
4.60
34
This list above is a fictional dataset containing an Football player's height, weight, their 40 yard run time in seconds and their vertical jump height in inches.
Each columns of height, weight, 40 yard dash time and vertical jump height can be studied individually as One Variable Data.
Example
Given the 10 player's 40-yard dash data, we can study and analyze as it one variable data analysis.
We could look at things like:
Slowest and Fastest Player
Average time elapsed between the 10 players
Two Variable Data
Can be called bivariate data
Data where each item has two characteristics (variables) measured at the same time.
We often use two variable data to find relationship or associations between the variables
Marcus “Tank” Doyle
198
4.78
DeShawn Rivers
185
4.41
Blake Armstrong
191
4.54
Jamal “Jet” Carter
178
4.29
Trevor McKnight
195
4.65
Andre Lopez
183
4.50
Colton “Crusher” Hayes
200
4.89
Malik Jefferson
188
4.42
Jared “Lightning” Cole
180
4.31
Ethan Brooks
193
4.60
The dataset we have seen prior has been shrunk down, but also arranged so that we are creating a two variable dataset.
This table can be used to study the relationship between a player's height and their 40-yard dash speed.
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