A Scatter Diagram, also called a scatter plot, is a picture that shows how two factors relate to each other. It is often used in data analysis and quality control to see how two sets of data relate to each other.
Each point in a scatter map is a single observation or piece of data. One of the variables is shown on the horizontal axis, and the other is shown on the vertical axis. Each point on the graph shows the values of the two variables for that observation by where it is on the graph.
The scatter map is used to see if there is a connection between the two things being looked at. If there is a connection, the arrangement of the points on the graph may make a shape that you can recognize, like a line or curve. If there is no link between the points, they will be spread out randomly across the line.
Scatter maps can be used for many different things, such as:
Finding trends: A scatter plot can be used to find trends or patterns in the data, such as a positive or negative association between two factors.
How to find outliers: Outliers are data points that are very different from the rest of the data. You can use a scatter plot to find outliers and figure out why they are happening.
Quality control: Scatter graphs can be used to keep an eye on quality control processes by looking at how different process factors relate to each other.
Overall, the scatter diagram is a useful tool for figuring out how two factors relate to each other and finding trends or patterns in the data. It can help find possible problems or places to improve, which can then be fixed to improve the quality of the data or process being analysed as a whole.
Key Points
– Visual Relationships: A scatter diagram shows the relationship between two sets of data by placing points on a graph.
– Data Comparison: It helps in seeing if there’s a connection between two variables like sales and advertising spending.
– Patterns Identification: It allows spotting trends, clusters, or correlations in the data.
– Easy Interpretation: By plotting points, it makes it easier to understand if there’s any connection between the variables being examined.
– Visual Clarity: The graph can display data points that might otherwise be hard to discern in raw data.
