T-Interval Calculator
Calculate a two-sided Student's t confidence interval for a population mean with unknown sigma.
Description
Calculate a two-sided Student's t confidence interval for a population mean with unknown sigma.
T-Interval Calculator is a focused tool for the following task. Calculate a two-sided Student's t confidence interval for a population mean with unknown sigma. It reports Lower bound, Upper bound, Margin of error, Critical t value, Degrees of freedom from the values you provide rather than inventing measurements, coefficients, or professional judgment that are not part of the input.
When to use T-Interval
Use this calculation to reproduce a defined quantitative method when the observations, units, sampling process, and assumptions match the method shown here.
- Sample mean
- Required number.
- Sample standard deviation
- Required number.
- Sample size
- Required integer.
- Confidence level
- Optional number.
The cited overview of Statistics supplies background for the terminology and domain context used by this tool.1
How T-Interval works
Calculate a two-sided Student's t confidence interval for a population mean with unknown sigma. Inputs are interpreted exactly in the displayed units and the calculation returns the following fields without presentation rounding.
- Lower bound
- Returned number.
- Upper bound
- Returned number.
- Margin of error
- Returned number.
- Critical t value
- Returned number.
- Degrees of freedom
- Returned integer.
Limitations and assumptions
- A numerical result does not by itself establish data quality, causation, representativeness, independence, distributional fit, or practical significance.
- Sample size must be at least 2.
- Sample standard deviation must be at least 0.
- Use finite inputs in the displayed units, preserve source measurements and assumptions, and independently verify consequential decisions.
Alternative or Complementary approaches
Inspect the underlying data, visualize its distribution, report uncertainty and sample size, and compare the result with a robust or domain-specific method where appropriate.
References
-
Statistics — Wikipedia contributors
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