The test measures a particular discrepancy between entered observations and a fitted or specified null pattern.
largest or summarized discrepancy
1EnterProvide the known values
2CalculateResults update automatically
3VerifyReview the details and units
Try an example
Enter plain numbers without measurement units. Datasets accept commas, spaces, semicolons, or line breaks and are limited to 10,000 values. Results stay in this browser.
Statistics result
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Linear Regression Significance Test. The observed effect is scaled by its null-model uncertainty and located on a reference distribution selected before looking at the result.
1State H₀, the effect, and direction2Calculate the statistic under H₀3Report p-value with effect and interval
Test statistic and reference model
t=b₁/SE(b₁), df=n−2; R²=SSR/SST.
The slope test evaluates a linear association conditional on the model, not causation or predictive validity elsewhere.
Responsible interpretation
A p-value is not the probability that the null is true, the chance the result occurred ‘by luck,’ or a measure of effect size, importance, replication, bias, or causation.
Required assumption: Errors should be independent, constant-variance and approximately normal for small-sample inference; inspect residual structure.
Quick guide
How to use this calculator
Enter the observations, probabilities, model parameters, or summary statistics requested by the visible labels.
Keep every value on the same scale and confirm that the selected sampling relationship, distribution, and tail convention match the question you are investigating.
Read the result together with its assumptions and interpretation. Statistical output summarizes uncertainty under a model; it does not repair biased data or establish causation.
Calculation method
How the linear regression significance test calculator works
t=b₁/SE(b₁), df=n−2; R²=SSR/SST.
The slope test evaluates a linear association conditional on the model, not causation or predictive validity elsewhere.
Worked example
Linear Regression Significance Test example
Paired observations produce a fitted intercept, slope, residual error, R², t statistic and p-value.
t=b₁/SE(b₁), df=n−2; R²=SSR/SST.
Supported inputs
Precision and limits
Model and design
Errors should be independent, constant-variance and approximately normal for small-sample inference; inspect residual structure.
Numerical scope
Inputs use double-precision numerical methods with guarded domains. Datasets accept up to 10,000 finite plain-decimal values. Extremely large parameters or probabilities deep in a numerical tail may require specialist statistical software.
Interpretation
The slope test evaluates a linear association conditional on the model, not causation or predictive validity elsewhere.
Decision boundary
The calculator does not validate how data were collected, diagnose dependence or bias, choose a scientifically meaningful effect, or replace review by a qualified statistician for consequential research, medical, regulatory, safety, or policy decisions.
Privacy
Entered values and calculated results stay in this browser and are not sent to an analytics service.
