wunder beta📘 Start with a scatterplot
Correlation describes how two quantitative variables move together in a roughly linear pattern. Begin with a scatterplot, where each point represents one paired observation. Look for direction, form, strength, clusters, and unusual points b
What you’ll learn
- Read scatterplotsRead direction, strength, and form before interpreting r.Plot first; a linear summary can hide curvature, clusters, and outliers.
- Resist causal claimsSeparate association from causation and report design limits.Name confounders and write conclusions no stronger than the evidence supports.
Questions this course answers
What does a correlation coefficient describe?
Correlation summarizes direction and strength for a linear relationship; it does not establish causation.
Why should you inspect a scatterplot before interpreting r?
The visual pattern shows whether a linear summary is sensible and whether unusual points are influential.
Which statement is a causal overclaim?
A shared cause or other explanation can produce an association without one variable causing the other.
What is a confounder?
A confounder can create or distort the apparent relationship between an exposure and an outcome.
What belongs in a cautious correlation conclusion?
A useful conclusion reports the pattern and uncertainty without claiming more than the design supports.
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