How to read this chart
Each X value from 1 through 4 appears twice. The Y pairs are (2, 4), (1, 5), (1, 5) and (2, 4). Each pair has mean Y = 3, so the overall mean is 3 and the centred cross-products sum to zero.
The least-squares line is horizontal at Y = 3. Pearson r and the fitted slope are both zero, but the vertical spread differs across X positions. A single coefficient does not describe all structure in a scatter plot.
Try the calculation yourself
Compare this example with the curved relationship example in this collection. Both have zero linear correlation, yet their point patterns differ. Look at the scatter before choosing a summary, and keep repeated X observations as separate pairs.
Open this exact example, change the data or calculation settings, and compare the result. The CSV preserves the input rows; the ECharts JSON contains drawing options.
What this example cannot tell you
These points were deliberately balanced; they are not a random sample demonstrating independence. A zero sample correlation can also result from noise, cancellation or a nonlinear pattern. It cannot establish the absence of every possible relationship.
Can I conclude the variables are independent?
No. Independence is a statement about the joint distribution, and zero linear correlation is insufficient to establish it. This small constructed sample only demonstrates how the Pearson calculation can equal zero when positive and negative contributions cancel.
Calculation convention
Every row supplies one X and one Y measurement for the same observation. The chart does not sort, merge or connect the points. Repeated X values are allowed and repeated pairs remain in the data, although exact overlaps can appear as one mark. Use consistent units and keep subject matching intact before importing.
Method background: NIST: scatter plot interpretation.
Created by SupaMakers for ChartsAI · September 8, 2026. Source and reuse terms.
