Variables
A response variable measures the outcome of a study. When plotting on a scatter plot, the response variable will be the y-axis. The response variable is similar to the dependent variable.
An explanatory variable helps explain or predict change in a response variable. This will be plotted on the x-axis. The explanatory variable is similar to the independent variable.
A quantitative variable is a variable that holds a numerical value that can be measured. For example, height, weight, length, and time are all quantitative variables.
A categorical variable is a variable that holds categories or labels which the data can be placed into. For example, race, educational level, and eye color are categorical variables. It is important to keep in mind that not all numerical variables are quantitative. Zip codes are an example of numerical values that are categorical variables.
Scatter plot
A scatter plot is a graphical representation of the relationship between two quantitative variables. Use the acronym DOFS when describing a scatter plot.
Direction: How is the overall pattern moving left to right? Is there a positive or negative association?
Outliers: Are there any clear outliers in the data?
Form: Is the pattern curved? Linear? Are there clusters of data?
Strength: How closely do the points follow a clear form?
Important note: You must ALWAYS label your axis with a title and units. You will lose points on the AP exam if you forget to do this, so make sure you scan all your graphs at the end to ensure you won’t lose easy points. In general statistics, labeling your graph makes it easier for you (or anyone else) to understand the data more effectively, so they can use it for their own calculations.