--- title: "Scatter Graphs & Correlation" description: "Describe simple mathematical relationships between two variables using scatter graphs, identify positive, negative, or no correlation, and use a line of best fit to make predictions" canonical: https://lightmysky.com/learn/mathematics/scatter-graphs-and-correlation-mt_8atyuvPUZc source: https://lightmysky.com/learn/mathematics/scatter-graphs-and-correlation-mt_8atyuvPUZc.md retrieved: 2026-10-19 --- > **Agent view.** This is the Markdown twin of the page, for tools and assistants. > When to use this site, and the call that answers each job: https://lightmysky.com/agent-instructions.md > API description (OpenAPI 3.1): https://lightmysky.com/openapi.json · Authentication: https://lightmysky.com/auth.md > Pricing: https://lightmysky.com/pricing.md · Catalog: https://lightmysky.com/llms.txt · Full catalog: https://lightmysky.com/llms-full.txt > Every machine-readable file on this domain: https://lightmysky.com/.well-known/ai-catalog.json > Ask for Markdown with `Accept: text/markdown`, a `.md` address, or `?mode=agent`. # Scatter Graphs & Correlation Describe simple mathematical relationships between two variables using scatter graphs, identify positive, negative, or no correlation, and use a line of best fit to make predictions Subject: Mathematics · Area: Data & Statistics · Ages 13 to 14 Page: https://lightmysky.com/learn/mathematics/scatter-graphs-and-correlation-mt_8atyuvPUZc ## Ready when they can - Plot bivariate data on a scatter graph and describe the type of correlation observed - Draw a line of best fit by eye and use it to estimate a value within the data range - Explain what positive, negative, and no correlation mean in the context of real data (e.g., temperature vs. ice-cream sales) ## Lesson: Scatter Graphs and Correlation A scatter graph shows how two things might be connected. Each point stands for one person or one item, plotted using two measurements at once, like hours of sleep and test score. You already know how to plot a point using an x-value and a y-value. A scatter graph just uses many of those points together to look for a pattern. **Example.** Priya asks eight classmates how many hours they revised and what score they got out of 20. She plots each classmate as one point: hours revised on the x-axis, score on the y-axis. Looking at all eight points, she sees them climb upward from left to right. That upward trend is called positive correlation. More revision tends to go with a higher score. *(drawing: Four of Priya's points: 1 hour with a score of 6, 2 hours with 9, 3 hours with 11, 4 hours with 14. The bars climb from left to right, just like her points. That climbing pattern is positive correlation.)* Correlation just describes the pattern in the points. Positive correlation means as one variable goes up, the other tends to go up too, like temperature and ice-cream sales. Negative correlation means as one goes up, the other tends to go down, like the age of a used car and its price. No correlation means there is no clear pattern at all, like shoe size and test scores. A correlation is not proof of a cause. On a wet day more umbrellas go up and more buses run late, so the two rise together, but no umbrella ever delayed a bus. The rain is doing both. Before you say one thing causes the other, look for a third thing that could be moving them together. *(drawing: The rain is the third thing here. It pushes umbrellas up and buses behind schedule at the same time, so the two correlate without either one causing the other.)* Once the points are plotted you can draw a line of best fit: one straight line through the middle of them, with roughly as many points above as below. It follows the overall trend rather than joining the dots bump by bump. To estimate with it, find your value on one axis, trace across to the line, then read off the other. That works inside the range you plotted; past the ends of your data you cannot tell whether the pattern keeps going. **Recap.** Points trending up mean positive correlation, points trending down mean negative correlation, scattered points mean no correlation, a line of best fit shows the overall trend, and none of it proves that one thing causes the other. ## Practice 14 questions on this page, each with its working shown. ## Needs first - [Statistical analysis vocabulary](https://lightmysky.com/learn/mathematics/statistical-analysis-vocabulary-mt_fmm-P17Vka) - [Coordinates (age 11+)](https://lightmysky.com/learn/mathematics/coordinates-age-11-mt_hVpGOEz2kG) - [Linear Function Graphs](https://lightmysky.com/learn/mathematics/linear-function-graphs-mt_WBdHkc2HTf) - [Comparing data sets with averages and range](https://lightmysky.com/learn/mathematics/comparing-data-sets-with-averages-and-range-mt_XSXnTQoQ4l) ## Opens up - [Lines of Best Fit: Prediction and Its Limits](https://lightmysky.com/learn/mathematics/lines-of-best-fit-prediction-and-its-limits-mt_CnYCx1a0j5) - [Correlation and the Product-Moment Coefficient](https://lightmysky.com/learn/mathematics/correlation-and-the-product-moment-coefficient-mt_Rs_Z0P7ELJ)