T test as a parametric statistic
In statistic tests, the probability distribution of the statistics is important. When samples are drawn from population N (µ, σ2) with a sample size of n, the distribution of the sample mean X̄ should be a normal distribution N (µ, σ2/n). Under the null hypothesis µ = µ0, the distribution of statist...
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| Format: | Article |
| Language: | English |
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Korean Society of Anesthesiologists
2015-12-01
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| Series: | Korean Journal of Anesthesiology |
| Subjects: | |
| Online Access: | http://ekja.org/upload/pdf/kjae-68-540.pdf |
| Summary: | In statistic tests, the probability distribution of the statistics is important. When samples are drawn from population N (µ, σ2) with a sample size of n, the distribution of the sample mean X̄ should be a normal distribution N (µ, σ2/n). Under the null hypothesis µ = µ0, the distribution of statistics z=X¯-µ0σ/n should be standardized as a normal distribution. When the variance of the population is not known, replacement with the sample variance s2 is possible. In this case, the statistics X¯-µ0s/n 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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| ISSN: | 2005-6419 2005-7563 |