One Sample Sign Test Calculator
Counts observations above and below a hypothesized median and applies an exact two-sided binomial test. The form displays exact binomial count above and below m0 beside one-sample sign test, using a worked condition that can be recalculated with the labeled inputs.
Describe the observed sample for the stated inputs
One-sample sign test
Scope of the one sample sign test method
The one sample sign test page counts observations above and below a hypothesized median and applies an exact two-sided binomial test.
One-sample sign test is limited to the statistical quantity named by the result panel. The one-sample sign test calculation does not silently add a population, time horizon, causal direction, or decision threshold that is absent from the fields.
Inputs that define one-sample sign test
- Sample values: For one-sample sign test, the displayed sample values sequence is 12, 15, 18, 18, 21, 24, 27, 30. Preserve sample values order when one-sample sign test depends on pairing, lag, rank, or time position, and distinguish an observed zero from a missing sample values entry.
- Hypothesized median: For one-sample sign test, the worked value for hypothesized median is 18. Treat the hypothesized median entry (18) explicitly as a count, proportion, rate, estimate, or model parameter before comparing one-sample sign test conditions.
The entries used for one-sample sign test must refer to one coherent analysis condition. Combining incompatible populations, periods, or measurement definitions can produce valid one-sample sign test arithmetic for a nonexistent study.
The arithmetic used for one-sample sign test
For one-sample sign test, match every symbol in the relationship to a labeled field before substituting numbers. One-sample sign test is reported in the scale implied by the inputs and formula.
While checking one-sample sign test, use sample values observations from one defined analysis set rather than totals copied from incompatible groups.
A reproducible one sample sign test case
The default one-sample sign test condition is Sample values = 12, 15, 18, 18, 21, 24, 27, 30, Hypothesized median = 18.
The example has four positive, two negative, and two tied observations; the exact p-value is 0.6875.
The live calculator reports Positive differences 4 · Negative differences 2 · Ties omitted 2 · Exact two-sided p-value 0.6875. Repeating one intermediate step from exact binomial count above and below m0 provides a fixed one-sample sign test reference check for later code changes.
Conditions attached to one-sample sign test
Values exactly equal to the null median are omitted, so the effective sample size may be smaller than the entered list.
For one sample sign test, a p-value measures compatibility with a stated null model; it is not the probability that the null hypothesis is true and it does not measure practical importance.
A nearby method may answer the next question: kruskal wallis test and runs test for randomness.
When one-sample sign test can mislead
When interpreting one sample sign test, pair the test result with the effect direction, effect size, uncertainty, sampling design, and the rule used for one-sided or two-sided inference.
As a second check for one-sample sign test, outliers, ties, ordering, and missing entries can affect one-sample sign test even when the number of observations stays unchanged.
Mistakes to avoid in the one sample sign test setup
Before accepting one-sample sign test, compare every entered value with its label, unit, and allowed domain after reading the printed relationship from left to right.
For one-sample sign test, do not substitute zero for an unobserved value; missingness and a measured zero describe different data.
Another one-sample sign test failure occurs when a rounded output is reused as though it were the original measurement. Carry guard digits through calculations that depend on one-sample sign test, then round only the reported value.
What to record with one-sample sign test
Report one-sample sign test using exact binomial count above and below m0, followed by the entered values, units, exclusions, and analysis date. Name the one-sample sign test population or dataset boundary instead of leaving it implicit.
Keep the full calculator output with the record, including Positive differences 4 · Negative differences 2 · Ties omitted 2 · Exact two-sided p-value 0.6875. A later one-sample sign test review can then distinguish a changed input from a different convention or software implementation.
Questions about one-sample sign test
What should be saved with one-sample sign test?
Save the entered values and units for sample values, hypothesized median, along with the analysis date, exclusions, software or formula version, and the relationship exact binomial count above and below m0. That record is sufficient to rebuild this specific one-sample sign test calculation.
Does one-sample sign test establish a causal or population conclusion?
No. The displayed one sample sign test value is conditional on the entered data and named method. The one-sample sign test design, measurement process, and assumptions determine what can be concluded beyond those values.
How should one-sample sign test be rounded?
Keep the unrounded one-sample sign test for subsequent arithmetic, then report only the precision supported by the source measurements and the decision context. Extra digits in one-sample sign test do not correct sampling or model error.
Which input deserves the closest boundary check?
For one-sample sign test, start with hypothesized median and then sample values. Confirm the one-sample sign test units and allowed domain because a valid-looking entry can still describe the wrong statistical setup.