The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
T test as a parametric statistic
Open accessAbstract
In statistic tests, the probability distribution of the statistics is important. When samples are drawn from population N (µ, σ(2)) with a sample size of n, the distribution of the sample mean X̄ should be a normal distribution N (µ, σ(2)/n). Under the null hypothesis µ = µ0, the distribution of statistics [Formula: see text] should be standardized as a normal distribution. When the variance of the population is not known, replacement with the sample variance s (2) is possible. In this case, the statistics [Formula: see text] follows a t distribution (n-1 degrees of freedom). An independent-group t test can be carried out for a comparison of means between two independent groups, with a paired t test for paired data. As the t test is a parametric test, samples should meet certain preconditions, such as normality, equal variances and independence.
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Citations
Cites
An Approximate Distribution of Estimates of Variance Components
Satterthwaite, F. E. (1946) · Biometrics Bulletin · doi:10.2307/3002019 · Cited by 4,373
The Importance of the Normality Assumption in Large Public Health Data Sets
Lumley, T., Diehr, P., Emerson, S., & Chen, L. (2002) · Annual Review of Public Health · doi:10.1146/annurev.publhealth.23.100901.140546 · Cited by 1,803
Cited by
Central limit theorem: the cornerstone of modern statistics
Kwak, S. G., & Kim, J. H. (2017) · Korean Journal of Anesthesiology · doi:10.4097/kjae.2017.70.2.144 · Cited by 1,062
More about the basic assumptions of t-test: normality and sample size
Kim, T. K., & Park, J. H. (2019) · Korean Journal of Anesthesiology · doi:10.4097/kja.d.18.00292 · Cited by 208
“Assuming that sample group 1 is the experimental group and sample group 2 is the control group, the t- statistic can be expressed as [6]”
MethodSelf-citationAfzaal, M., Nouri, J., Zia, A., Papapetrou, P., Fors, U., Wu, Y., Li, X., & Weegar, R. (2021) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2021.723447 · Cited by 125
Tips for troublesome sample-size calculation
In, J., Kang, H., Kim, J. H., Kim, T. K., Ahn, E. J., Lee, D. K., Lee, S., & Park, J. H. (2020) · Korean Journal of Anesthesiology · doi:10.4097/kja.19497 · Cited by 55
Self-citationBhatia, S., Gandhi, T., Kumar, D., & Jalote, P. (2024) · Proceedings of the 1st International Workshop on Large Language Models for Code · doi:10.1145/3643795.3648396 · Cited by 55
Metadata
- Authors
- Kim, T. K.
- Venue
- Korean Journal of Anesthesiology
- Published
- 2015
- Volume
- 68
- Issue
- 6
- Pages
- 540
- ISSN
- 0302-5780 (ISSN-L)
- 2005-6419
- 2005-7563
- OpenAlex
- W2183659962
- Cited by
- 1,436
- References
- 2
- FWCI
- 17.52
- Type
- journal article
- Language
- en
- Open access
- diamond
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