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T-score-kalkylator

Beräkna t-statistikan för ett stickprov.

Introduktion

T-Score Calculator — Compute the one-sample t-statistic. Enter Sample mean, Population mean, Sample std. deviation, Sample size to get an instant, accurate result.

Formel

One-sample t-statistic: t = (sample mean − population mean) / (sample standard deviation / √n).

Steg för steg

  1. Enter the Sample mean.
  2. Enter the Population mean.
  3. Enter the Sample std. deviation.
  4. Enter the Sample size.
  5. Click Calculate to see your result instantly.

Verkligt exempel

Example: With Sample mean = 52, Population mean = 50, Sample std. deviation = 5, Sample size = 25, the T-Score Calculator gives T Score: 2.

Vanliga Frågor

What is the t-score used for?
It measures how many standard errors your sample mean is from a hypothesized population mean, commonly used in one-sample t-tests.
How is this different from a z-score?
A t-score is typically used when the population standard deviation is unknown and estimated from the sample, and it accounts for sample size via degrees of freedom when compared against a t-distribution.
What inputs does the T-Score Calculator need?
You'll need to provide: Sample mean, Population mean, Sample std. deviation, Sample size. All fields use sensible defaults, so you can see a working example immediately and then adjust the values to match your own numbers.
How accurate is the T-Score Calculator?
The T-Score Calculator applies the formula exactly as calculated — One-sample t-statistic: t = (sample mean − population mean) / (sample standard deviation / √n). — so results are precise for the inputs you provide. Accuracy depends on entering correct, realistic input values.
Is the T-Score Calculator free to use?
Yes, the T-Score Calculator is completely free, requires no signup, and runs instantly in your browser.

Om T-score-kalkylator

The T-Score Calculator uses a real, verifiable formula — One-sample t-statistic: t = (sample mean − population mean) / (sample standard deviation / √n). — so results are accurate every time, not an approximation.