A scatter plot is a type of graph used to display values for two variables, represented by points on a Cartesian plane. It is useful for visualizing the relationship between two quantitative variables and identifying patterns, correlations, or trends.
Key Fields of a Scatter Plot
Represents a categorical or continuous variable that serves as the context for the data points on the scatter plot. This dimension is not directly plotted on the X or Y axes but can be used to group or filter the data. Helps in understanding how the relationship between the X and Y variables changes across different segments or categories.
Categories such as time periods (e.g., months, years), geographical regions, cities or different product types.
Represents one of the quantitative variables and is plotted horizontally on the scatter plot. On the X-axis, this variable shows the values for which you are measuring the corresponding Y values. Helps in understanding how changes in this variable affect the corresponding Y values.
Metrics such as time (e.g., days, months), temperature readings, or sales amounts.
Represents the other quantitative variable and is plotted vertically on the scatter plot. On the Y-axis, this variable shows the values corresponding to the X-axis values. Helps in analyzing how this variable changes in relation to the X-axis values.
Metrics such as revenue, performance scores, profit or measurements like temperature.
You can display a maximum of One Dimension, One X-Axis, and One Y-Axis in your chart/table.
When to Use a Scatter Plot:
Ideal for examining the relationship or correlation between two quantitative variables. Helps in determining if there is a positive, negative, or no correlation.
Useful for identifying trends, clusters, or outliers in the data. This can reveal patterns or anomalies that are not immediately obvious from other types of charts.
When the dimension is used to group data, scatter plots can show how relationships between variables differ across categories or segments.