Answer:
scatter plot
Explanation:
A scatter plot is used to determine if there is a relationship between two variables; for example x and y. We use x and y because the plot is drawn on the Cartesian plane which shows the values for x along the horizontal axis and the values for y along the vertical axis. To construct the plot you need multiple coordinates (x;y pairings) that will lie on the Cartesian plane.
You are given multiple coordinates or x and y pairings (x;y) that represent the data for each individual. Place a dot on corresponding values on the Cartesian plane. When you do the same for each data point (x;y) you will see a pattern forming which represents the type of relationship that exists between the two overall variables. This is usually a linear pattern: this doesn't mean the dots form a line though.
This data is called "paired" because each x and y value belongs to the same individual. We bring together all of the data for the different individuals to determine if there is some kind of pattern or relationship between two overall variables: either a positive, negative or no relationship. This relationship is more formally known as the "correlation" between the variables:
A: positive correlation: the y value tends to increase as the x value increases
B: negative correlation: the y value tends to decrease as the x value increases (move in the opposite direction)
C: no correlation: a random pattern, neither positive or a negative relationship
NB: The plot depicts a linear relationship
An example:
For example, you want to see if there is a correlation (relationship) between the shoe size and height of children in a school:
Your individuals whose data you are collecting are the school children.
The y axis will be height and the x axis can be the shoe size (your two variables).
Each person has a different combination of height and shoe size which together make a coordinate (x;y). Eg. (6;170) this means that this person has a shoe size of 6 and height of 170. Find the corresponding point of the Cartesian plane and do the same for the rest of the students. Soon you will see a pattern forming. You follow along the x and y axis to see whether the variables increase together or not.
Lets say for this example the height of the students increases as the shoe size increases then we can conclude that overall at this school, the shoe size and height of students has a positive linear relationship.