🎓 Graphing & Visualization • Statistical Charts
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Scatter Plot & Linear Regression Generator
Creates bivariate scatter plots and calculates best-fit linear regression equations with Pearson correlation coefficients.
Bivariate Data Pairs (x, y separated by commas and semicolons):8 pairs loaded
Presets:
Regression Equationŷ = 1.50x + 0.88Slope m = 1.501
Pearson r0.999Very Strong Positive
R² Determination0.99999.9% explained
Standard Error Se±0.146Residual variance
Linear Model Forecasting & Prediction Tool
Given input x =Estimated ŷ =14.39(Estimated confidence band: [14.1, 14.68])
What is a Scatter Plot?
A scatter plot uses Cartesian coordinates to display values for two variables from a dataset, showing how one variable may be correlated with another.
Formula & Step-by-Step Calculation
y = mx + b, r = (n·Σxy - Σx·Σy) / √([n·Σx² - (Σx)²][n·Σy² - (Σy)²])
Least-squares linear regression and Pearson correlation coefficient.
Worked Step-by-Step Examples
Example 1
Study hours vs exam marks: (1,2), (2,3.5), (3,5.1), (4,6.8), (5,8.2)
Solution: Strong positive correlation (r ≈ 0.999), Trendline y = 1.55x + 0.43
• Positive slope indicates increasing exam scores with increased study time
Common Real-World & Academic Use Cases
- ✓ Scientific experimental data correlation testing
- ✓ Economic econometric trend forecasting
- ✓ Machine learning regression modeling
How to Use the Scatter Plot & Linear Regression Generator
1
Enter (x, y) Pairs
Input data points separated by semicolons.
2
Inspect Trendline
View the fitted linear regression line and correlation r.
Frequently Asked Questions
Q: What does a Pearson r near 1.0 mean?
An r close to +1.0 indicates a very strong positive linear relationship between the two variables.