Scatter Plot Generator

Turn your paired data into a scatter plot in seconds. Enter your X values and Y values as comma-separated numbers, add an optional chart title and axis labels, and choose whether to overlay a line of best fit. You get a rendered scatter graph plus key statistics: correlation coefficient (r), slope, intercept, and number of data points.

Enter your independent (horizontal axis) values separated by commas.

Enter your dependent (vertical axis) values separated by commas. Must match the count of X values.

Overlay a linear regression trendline on the scatter plot.

Results

Correlation Coefficient (r)

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Number of Data Points

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Slope (m)

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Intercept (b)

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R² (Coefficient of Determination)

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Correlation Strength

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Scatter Plot

Results Table

Frequently Asked Questions

What is a scatter plot?

A scatter plot (also called an XY graph) is a type of data visualization that displays pairs of values as individual points on a two-dimensional grid. The horizontal axis represents the independent variable (X) and the vertical axis represents the dependent variable (Y). It's commonly used to identify relationships, trends, or correlations between two variables.

How do I use this scatter plot generator?

Enter your X values and Y values as comma-separated numbers in the respective input boxes — for example, '1, 2, 3, 4' and '2, 4, 5, 7'. Both lists must have the same number of values. Optionally add a chart title and axis labels, then click Generate. The scatter plot and regression statistics are produced immediately.

What is a line of best fit (trendline)?

A line of best fit, or linear regression line, is a straight line drawn through a scatter plot that best represents the overall trend of the data. It minimizes the sum of squared residuals (the vertical distances between each point and the line). Enable the 'Show Line of Best Fit' option to overlay this line on your chart.

What does the correlation coefficient (r) mean?

The correlation coefficient (r) measures the strength and direction of the linear relationship between X and Y. Values range from −1 to +1. A value near +1 indicates a strong positive correlation, near −1 indicates a strong negative correlation, and near 0 indicates little to no linear relationship. Generally, |r| > 0.7 is considered strong, 0.4–0.7 moderate, and below 0.4 weak.

What is R² and how is it different from r?

R² (the coefficient of determination) is the square of the correlation coefficient r. It represents the proportion of variation in Y that can be explained by the linear relationship with X. For example, R² = 0.85 means 85% of the variability in Y is accounted for by the regression line. While r shows direction and strength, R² focuses purely on explanatory power.

How do I interpret the slope and intercept?

The slope (m) tells you how much Y changes for every one-unit increase in X. A positive slope means Y increases as X increases; a negative slope means Y decreases. The intercept (b) is the predicted value of Y when X equals zero — the point where the regression line crosses the Y-axis. Together, they define the equation ŷ = mx + b.

What if my X and Y lists have different lengths?

Both lists must contain the same number of values. If they differ, the tool will alert you and will not generate the plot. Check for missing commas, extra spaces, or unequal entries. Each X value must correspond to exactly one Y value.

Can I use negative numbers or decimal values?

Yes — the scatter plot generator fully supports negative numbers (e.g. '-3, -1, 2, 5') and decimal values (e.g. '1.5, 2.7, 3.14'). Simply enter them as comma-separated values in the input boxes. The axes will automatically scale to fit your data range.

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