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Small size sampling

机译:小尺寸采样

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摘要

Based on the law of large numbers which is derived from probability theory, we tend to increase the sample size to the maximum. Central limit theorem is another inference from the same probability theory which approves largest possible number as sample size for better validity of measuring central tendencies like mean and median. Sometimes increase in sample-size turns only into negligible betterment or there is no increase at all in statistical relevance due to strong dependence or systematic error. If we can afford a little larger sample, statistically power of 0.90 being taken as acceptable with medium Cohen's d (<0.5) and for that we can take a sample size of 175 very safely and considering problem of attrition 200 samples would suffice.
机译:基于源自概率论的大数定律,我们倾向于将样本量增加到最大。中心极限定理是同一概率理论的另一个推论,该理论批准最大可能数作为样本大小,以更好地测量中心趋势(例如均值和中位数)。有时,由于强大的依赖性或系统性误差,样本数量的增加只会带来微不足道的改善,或者统计相关性根本没有增加。如果我们能够提供更大的样本,则在中等Cohen d(<0.5)的情况下,统计学上可以接受0.90的幂,并且为此,我们可以非常安全地选择175的样本量,并考虑消耗200个样本的问题就足够了。

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