Univariate and Bivariate Data
Univariate: one variable, Bivariate: two variables
Univariate means "one variable" (one type of data)
Example: Travel Time (minutes): 15, 29, 8, 42, 35, 21, 18, 42, 26
The variable is Travel Time
We can do lots of things with univariate data:
- Find a central value using mean, median and mode
- Find how spread out it is using range, quartiles and standard deviation
- Make plots like Bar Graphs, Pie Charts and Histograms
Bivariate means "two variables", in other words there are two types of data
With bivariate data you have two sets of related data that you want to compare:
Example:
An ice cream shop keeps track of how much ice cream they sell versus the temperature on that day.
The two variables are Ice Cream Sales and Temperature.
Here are their figures for the last 12 days:
| Ice Cream Sales vs Temperature | |
| Temperature °C | Ice Cream Sales |
|---|---|
| 14.2° | $215 |
| 16.4° | $325 |
| 11.9° | $185 |
| 15.2° | $332 |
| 18.5° | $406 |
| 22.1° | $522 |
| 19.4° | $412 |
| 25.1° | $614 |
| 23.4° | $544 |
| 18.1° | $421 |
| 22.6° | $445 |
| 17.2° | $408 |
And here is the same data as a Scatter Plot:
It is now easy to see that warmer weather leads to more sales, but the relationship is not perfect.
So with bivariate data we are interested in comparing the two sets of data and finding any relationships.
We can use Tables, Scatter Plots, Correlation, Line of Best Fit, and plain old common sense.