# 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

### Example: Puppy Weights

You weigh the pups and get these results:

2.5, 3.5, 3.3, 3.1, 2.6, 3.6, 2.4

The variable is Puppy Weight

We can do lots of things with univariate data:

Bivariate means "two variables", in other words there are two types of data

With bivariate data we have two sets of related data we 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:

Temperature °C Ice Cream Sales Ice Cream Sales vs Temperature 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:

Now we can easily see that warmer weather and more ice cream sales are linked, 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.