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1. Central Limit Theorem (CLT)
The Central Limit Theorem in Statistics states that as the sample size increases and its variance is finite, then the distribution of the sample mean approaches normal distribution irrespective of the shape of the population distribution.
The central limit theorem posits that the distribution of sample means will invariably conform to a normal distribution provided the sample size is sufficiently large. This holds regardless of the underlying distribution of the population, be it normal, Poisson, binomial, or any alternative distribution.
2.Sample Variance
3. t-distribution
t-distribution
4. confidence Interval
5. Hypothesis Test
6. Z=X-Y
7.Related equations
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- 作者:现代数学启蒙
- 链接:https://www.math1234567.com/article/inferentialstatistics
- 声明:本文采用 CC BY-NC-SA 4.0 许可协议，转载请注明出处。
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