Scatter Diagram Correlation

What is a scatter diagram?

A scatter diagram, also known as a scatter plot, is a graphical representation of the relationship between two quantitative variables. Each point on the scatter diagram represents an observation in the dataset, with one variable plotted on the x-axis and the other on the y-axis.

How can you determine the direction of the relationship using a scatter diagram?

Positive Relationship: If the points tend to rise from left to right, the relationship is positive, indicating that as one variable increases, the other variable also increases.

Negative Relationship: If the points tend to fall from left to right, the relationship is negative, indicating that as one variable increases, the other variable decreases.

No Relationship: If the points are randomly scattered with no discernible pattern, there is no clear relationship between the variables.

What are outliers in a scatter diagram?

Outliers are points that lie far away from the overall pattern of the data. They may indicate unusual observations or errors in the data.

Can scatter diagrams show non-linear relationships?

Yes, scatter diagrams can show non-linear relationships. If the points form a pattern that is curved or follows a non-linear trend, it indicates a non-linear relationship between the variables.

How can you enhance a scatter diagram to better interpret correlation?

You can enhance a scatter diagram by:

• Adding a Trend Line: A line of best fit (regression line) helps in visualizing the overall trend.
• Color-Coding Points: Use different colors to represent different groups or categories within the data.
• Annotating Outliers: Mark or label outliers to highlight unusual observations.
• Using Jitter: Add slight random noise to the points to better visualize dense clusters (helpful for large datasets).