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Range Restriction.

Narrow the selected range of one variable without changing its generating relationship.

Interactive experimentintuitiveField note ·
INTERACTIVE EXPERIMENT / P24

Range Restriction

Narrow the selected range of one variable without changing its generating relationship.

TEST THE MECHANISM

Generate a bivariate Normal teaching population with correlation 0.7, then restrict admission to a narrow band of the x variable. The underlying data-generating rule stays unchanged.

0.23
x and y in synthetic standard-deviation units
Selected observations
199
Full sample correlation
0.699
Restricted correlation
0.689

Restriction can reduce observed correlation without changing the generating relationship. Finite-sample fluctuations and the exact selection rule matter; this is not a formula for correcting a real admissions study.

Finite samples fluctuate and selection rules differ. The display is not a universal correction formula, causal claim or estimate of an actual admissions process.

THE SHORT VERSION

Range Restriction, explained.

Range restriction limits variation in a measured variable through selection and can alter an observed association within the selected sample.

01 / THE MECHANISM

Why it happens

A bivariate Normal teaching population has generating correlation 0.7. The reader retains observations with absolute x below a chosen bound and compares sample correlations before and after restriction.

Range restriction limits variation in a measured variable through selection and can alter an observed association within the selected sample.

Read the result

The same generated points remain in the background. Only the selected x range changes; population correlation and finite-sample correlation are separate quantities.

02 / FOLLOW IT THROUGH

A worked example

Select a narrow band without changing the process

  1. Begin with a broad absolute-x bound to retain most of the synthetic population.

  2. Narrow the bound and compare the restricted sample size and correlation with the full sample.

  3. Treat the change as conditional on this selection rule and finite sample rather than a universal correction factor.

OPTIONAL DEEPER DETAILGo deeper: inside the model

Inside this model

A bivariate Normal teaching population has generating correlation 0.7. The reader retains observations with absolute x below a chosen bound and compares sample correlations before and after restriction.

03 / BEYOND THE EXPERIMENT

Where this idea is useful

A practical use

Interpret a correlation among selected applicants in light of the range excluded by admission.

CHECK YOUR INTUITION

A common misconception

THE TEMPTING CONCLUSION

“A lower selected-sample correlation proves the original relationship weakened.”

THE MORE USEFUL DISTINCTION

Selection can reduce variable range and alter the observed association while leaving the generating mechanism unchanged.

What this explanation leaves out

  • Finite samples fluctuate and selection rules differ. The display is not a universal correction formula, causal claim or estimate of an actual admissions process.
ONE MORE QUESTION

Why is the displayed full correlation not exactly 0.7?

The generator uses population correlation 0.7, but two hundred realised observations have their own fluctuating sample correlation.

TAKE THE IDEA WITH YOU

Which part of the predictor’s range was excluded before your relationship was measured?

Associated thinkers

Associated withKarl Pearson ↗

Associations marked provisional are awaiting source review.

Further reading

Explore the original research or the teaching reference behind this experiment.