Is this scatter plot maker free?

Yes, the scatter plot maker is completely free to use and does not require sign-up.

Is my data uploaded to a server?

No. All data processing happens locally in your browser, ensuring full data privacy.

Scatter Plot Maker

Q: What is a scatter plot?

A scatter plot is a chart that shows the relationship between two numerical variables using points on a Cartesian plane.

Enter data to create beautiful scatter plots

Chart Data & Labels

Chart Title

Subtitle

X-Axis Label

Y-Axis Label

Series A Name

X Values (comma separated x1, x2, x3...)

Y Values (comma separated y1, y2, y3...)

X Points: 5Y Points: 5Valid Pairs: 5

Trendline Options

Show Trendline

Color

Style

Width: 2px

Export Chart

Choosing the Right Format:

PNG: Best for charts with transparency, lossless quality
JPEG/JPG: Smaller file size, good for charts without transparency
SVG: Vector format, perfect for high-quality prints and scalability

Perfect For:

Students & Academics: Biology, chemistry, physics lab reports
Business Analytics: Sales trends, market analysis, performance metrics
Research Projects: Statistical analysis and data visualization
Presentations: Meetings, conferences, webinars, and reports
Data Journalism: Creating visualizations for articles and stories
Educational Content: Teaching statistics and correlation concepts

Features:

Instant Scatter Plot Generation - Upload your data and get a clean, professional looking scatter plot in just seconds.
Fully Customizable Charts - Change colors, labels, titles, point size, and more tailor the chart to your style or brand.
Multiple Download Formats
Blazing Fast Performance
High Quality Chart Output
No Sign Up Required
Works on Any Device
We Do Not Store Your Data
Completely Free to Use

Understanding Scatter Plots & Regression Analysis

Scatter plots aren't just dots on a graph-they're powerful tools for spotting patterns, identifying outliers, and figuring out how two variables connect. Whether you're a student, researcher, or just curious about data, here's the math that powers every scatter plot creator.

1The Line of Best Fit (Linear Regression)

Ever wondered what that trendline on your scatter plot actually means? That's a regression line-basically the single straight line that best captures where your data is heading. Here's the classic equation you'll see:

y = mx + b

What each part means:

$y$ - The predicted value (what you're trying to figure out)
$m$ - The slope (how steep your line climbs or falls)
$x$ - Your input value
$b$ - The y-intercept (where your line hits the y-axis)

Real world example:

Say you're charting study hours against test scores. If your equation turns out to be $y = 8x + 40$ , that tells you each extra hour of study bumps your score by 8 points. Even with zero study time, you'd still score around 40 (maybe from paying attention in class!).

2Calculating the Slope

The slope is where it gets interesting. It tells you exactly how much y shifts whenever x changes by one unit. Positive slope? Both variables rise together. Negative slope? One goes up while the other drops-like ice cream sales vs. sweater purchases.

m = \frac{n\sum xy - \sum x \sum y}{n\sum x^2 - (\sum x)^2}

Breaking it down:

$n$ - Number of data points

$\sum xy$ - Sum of each x times its paired y

$\sum x$ and $\sum y$ - Sum of all x and y values

$\sum x^2$ - Sum of each x value squared

Don't stress about memorizing this formula-our scatter plot creator handles all the heavy lifting automatically when you toggle on trendlines.

3Finding the Y-Intercept

Got your slope? Finding the y-intercept is the easy part. It's simply the average y-value minus the slope multiplied by the average x-value:

b = \bar{y} - m\bar{x}

Here, $\bar{x}$ and $\bar{y}$ are just fancy notation for the averages of your x and y values. Think of the y-intercept as your starting point-what y equals when x is zero.

Real-world example: if you're plotting ad spend vs. sales revenue, the y-intercept shows your baseline sales before spending a single dollar on advertising.

4Correlation Coefficient (r)

Here's the real MVP of scatter plot analysis. The correlation coefficient (r) tells you exactly how tightly your two variables are connected-and whether that relationship is positive or negative:

r = \frac{n\sum xy - \sum x \sum y}{\sqrt{[n\sum x^2 - (\sum x)^2][n\sum y^2 - (\sum y)^2]}}

$r = +1$

Perfect positive correlation. As x increases, y increases proportionally.

$r = 0$

No correlation. The variables have no linear relationship.

$r = -1$

Perfect negative correlation. As x increases, y decreases proportionally.

Practical interpretation:

|r| > 0.7 - Strong relationship
0.4 < |r| < 0.7 - Moderate relationship
|r| < 0.4 - Weak relationship

5R-Squared (Coefficient of Determination)

R-squared is exactly what it sounds like: the correlation coefficient, squared. But here's why it's so useful-it tells you what percentage of y's variation can be explained by x:

R^2 = r^2

Why this matters:

When you see R² = 0.85, that means 85% of the ups and downs in your y-values can be traced back to changes in x. The other 15%? That's noise-other stuff you're not tracking.

Quick rule: R² above 0.5 generally means your trendline is telling a real story. Below that, you might just be seeing patterns in random noise.

Quick Tips for Better Scatter Plots

Do:

✓Label your axes with units (e.g., "Revenue (USD)")
✓Use transparency when points overlap
✓Check R² before trusting a trendline
✓Look for outliers - they tell interesting stories

Avoid:

✗Assuming correlation means causation
✗Forcing trendlines on random-looking data
✗Using rainbow color schemes (accessibility issue)
✗Overcrowding with too many data points

Frequently Asked Questions About Scatter Plot Maker

What is a scatter plot and when should I use one?+

A scatter plot is a graph that shows the relationship between two variables using dots or points. Each point represents an observation, with its position determined by its X and Y values. Scatter plots are ideal for identifying correlations, clusters, and outliers in datasets. They're commonly used in statistics, science, business analytics, and research to visualize relationships and patterns.

How do I enter data into the scatter plot maker?+

Simply enter your X values and Y values in the "Data" tab, separated by commas. For example: X values "10, 20, 30" and Y values "5, 15, 25". Each X value is paired with the corresponding Y value. The tool automatically validates your input and shows you the number of valid data pairs before you update the chart.

Can I add a trendline to my scatter plot?+

Yes! The trendline feature is available in the "Data" tab. Enable it to automatically calculate and display a linear regression line through your data points. You can customize the trendline color, style (solid, dashed, dotted), and width. This is especially useful for showing correlations and trends in your data.

What file formats can I download my scatter plot in?+

You can download your scatter plot in four formats: PNG (best for web and presentations with transparency), JPEG (smaller file size for compression), JPG (standard image format), and SVG (vector format perfect for printing and scaling). SVG is recommended for professional publications and large prints as it maintains quality at any size.

Is my data secure? Do you store my information?+

Absolutely. All data processing happens directly in your browser. We never upload, store, or access your data on any server. Your scatter plots and data remain completely private and secure. This is why you don't need to sign up or log in-we have nothing to store.

Can I customize the appearance of my scatter plot?+

Extensively! Use the "Style" tab to change marker colors and sizes, background color, text color, and legend position. The "Advanced" tab offers animation settings, grid customization, tooltip theming, and more. You can create a scatter plot that matches your brand, presentation style, or personal preference.