Correlation Test Power Calculator
Estimates approximate power for detecting a nonzero correlation. The form displays approximate Fisher-z power beside correlation test power, using a worked condition that can be recalculated with the labeled inputs.
Set the labeled inputs
Correlation Test Power
Purpose of this correlation test power calculation
The correlation test power page estimates approximate power for detecting a nonzero correlation.
Correlation Test Power is limited to the statistical quantity named by the result panel. The correlation test power calculation does not silently add a population, time horizon, causal direction, or decision threshold that is absent from the fields.
The surrounding workflow may also require anova effect size.
Before entering the correlation test power data
- Planned correlation: For correlation test power, the worked value for planned correlation is 0.35 correlation. Treat the planned correlation entry (0.35 correlation) explicitly as a count, proportion, rate, estimate, or model parameter before comparing correlation test power conditions. The form enforces minimum -0.999, maximum 0.999.
- Sample size: For correlation test power, the worked value for sample size is 50 observations. Treat the sample size entry (50 observations) explicitly as a count, proportion, rate, estimate, or model parameter before comparing correlation test power conditions. The form enforces minimum 5.
The entries used for correlation test power must refer to one coherent analysis condition. Combining incompatible populations, periods, or measurement definitions can produce valid correlation test power arithmetic for a nonexistent study.
From inputs to correlation test power
For correlation test power, match every symbol in the relationship to a labeled field before substituting numbers. Correlation Test Power is reported in the scale implied by the inputs and formula.
While checking correlation test power, change Planned correlation by a small controlled amount and predict the direction of correlation test power before recalculating.
Worked values for correlation test power
The default correlation test power condition is Planned correlation = 0.35 correlation, Sample size = 50 observations.
A correlation of .35 with n=50 gives an approximate power near 0.70.
The live calculator reports Approximate power 0.70724973. Repeating one intermediate step from approximate Fisher-z power provides a fixed correlation test power reference check for later code changes.
Limits on interpreting correlation test power
The Fisher transformation is an approximation and assumes independent paired observations with a stable association.
For correlation test power, power and design calculations are prospective scenarios, not guarantees. For correlation test power, their answer changes when the planned effect, variance, allocation, alpha, or attrition assumption changes.
When correlation test power can mislead
When interpreting correlation test power, report the design inputs as assumptions and compare at least one plausible alternative before committing resources to the plan.
As a second check for correlation test power, if that direction is surprising, recheck the units and the role of Sample size in approximate Fisher-z power before accepting the display.
Testing how stable correlation test power is
Change planned correlation while holding the remaining entries fixed, then state why the direction and size of the correlation test power change are plausible from approximate Fisher-z power.
Repeat the correlation test power exercise with sample size. If a modest defensible change materially alters the interpretation, report both conditions rather than presenting that correlation test power scenario as exact.
Where a plausible correlation test power can go wrong
Before accepting correlation test power, compare every entered value with its label, unit, and allowed domain after reading the printed relationship from left to right.
For correlation test power, do not move a number between fields merely because the units look compatible; each label gives the number a different statistical role.
Another correlation test power failure occurs when a rounded output is reused as though it were the original measurement. Carry guard digits through calculations that depend on correlation test power, then round only the reported value.
What to record with correlation test power
Report correlation test power using approximate Fisher-z power, followed by the entered values, units, exclusions, and analysis date. Name the correlation test power population or dataset boundary instead of leaving it implicit.
Keep the full calculator output with the record, including Approximate power 0.70724973. A later correlation test power review can then distinguish a changed input from a different convention or software implementation.
Questions about correlation test power
How should correlation test power be rounded?
Keep the unrounded correlation test power for subsequent arithmetic, then report only the precision supported by the source measurements and the decision context. Extra digits in correlation test power do not correct sampling or model error.
Which input deserves the closest boundary check?
For correlation test power, start with sample size and then planned correlation. Confirm the correlation test power units and allowed domain because a valid-looking entry can still describe the wrong statistical setup.
Why could another program report a different correlation test power?
A different convention for rounding, tails, ties, interpolation, parameterization, or missing values can change correlation test power. Compare the printed correlation test power formula and its input definitions before treating either output as wrong.
What does correlation test power represent on this page?
It is the quantity produced by approximate Fisher-z power from the displayed planned correlation, sample size. This page estimates approximate power for detecting a nonzero correlation.