{{ toc.name }}
{{ toc.signature }}
{{ toc.name }} {{ 'ml-btn-view-details' | message }}
{{ stepNode.name }}
Proceed to next lesson
Lesson
Exercises
Recommended
Tests
An error ocurred, try again later!
Chapter {{ article.chapter.number }}
{{ article.number }}. 

{{ article.displayTitle }}

{{ article.introSlideInfo.summary }}
{{ 'ml-btn-show-less' | message }} {{ 'ml-btn-show-more' | message }} expand_more
{{ 'ml-heading-abilities-covered' | message }}
{{ ability.description }}

{{ 'ml-heading-lesson-settings' | message }}

{{ 'ml-lesson-show-solutions' | message }}
{{ 'ml-lesson-show-hints' | message }}
{{ 'ml-lesson-number-slides' | message : article.introSlideInfo.bblockCount}}
{{ 'ml-lesson-number-exercises' | message : article.introSlideInfo.exerciseCount}}
{{ 'ml-lesson-time-estimation' | message }}

Concept

Bivariate Data

Bivariate data is a set of data that has been collected in two variables. It shows a relationship between the variables. Each data value in one variable corresponds to a data value in the other variable. A data set with the shoe sizes and heights of people is an example of bivariate data.
Shoe Size
Height (in.)

A scatter plot is used to represent bivariate data.

Scatter Plot of Bivariate Data
This scatter plot shows that tall people tend to have larger shoe sizes. Keep in mind that different data sets may have different types of relationships.

Extra

Relationship Between Data Sets
Two variables that change together might have different types of relationships — positive linear relationship, negative linear relationship, non-linear relationship, or no relationship.
Relationships Between Two Variables