The Single-Sample t Test
Abstract
The single-sample t test is employed in a hypothesis testing situation involving a single sample in order to determine whether or not a sample with a mean of X is derived from a population with a mean of μ. If the result of the single-sample t test yields a significant difference, the researcher can conclude there is a high likelihood the sample is derived from a population with a mean value other than μ The following two assumptions, which are noted for the single-sample z test, also apply to the single-sample t test: The sample has been randomly selected from the population it represents; and The distribution of data in the underlying population the sample represents is normal. If the value of f is computed for a specific sample size, the power of both the single-sample z test and the single-sample t test can be determined by using.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The text we found for this paper looks like another document, so the self-check wasn’t run.
Cites
Altman, D. G., Machin, D., Bryant, T. N., & Gardner, M. J. (2002). Statistics with confidence: Confidence intervals with statistical guidelines (2nd ed.). London: British Medical Journal Books.
(n.d.)
Unresolved
Flagged first, then by citations
1 of the 1 references couldn’t be matched to a known paper.
- Authors
- Sheskin, D. J.
- Corresponding author
- Sheskin, David J.
- Venue
- Handbook of Parametric and Nonparametric Statistical Procedures
- Publisher
- Chapman and Hall/CRC
- Published
- 2020-06-09
- Pages
- 163-210
- OpenAlex
- W4254199967
- Semantic Scholar
- 9ef8822b328e92c7e2720a5159b6d6666094f434
- Cited by
- 0
- References
- 1
- FWCI
- 0.00
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Chapman & Hall/CRC eBooks (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Probability and Statistical Research
- Physical Sciences › Mathematics › Statistics and Probability › Statistics Education and Methodologies
- Physical Sciences › Mathematics › Statistics and Probability › Probabilistic Statistics in Medicine
- Keywords
- hypothesis testing, sample mean, population mean, random sampling, normality assumption, statistical power
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-11.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
