Statistics 简明教程
Statistics - Best Point Estimation
点估计涉及使用样本数据来计算一个单值(称为统计量),该值用作未知(固定或随机)总体参数的“最佳猜测”或“最佳估计”。更正式地说,它将点估计器应用于数据。
Point estimation involves the use of sample data to calculate a single value (known as a statistic) which is to serve as a "best guess" or "best estimate" of an unknown (fixed or random) population parameter. More formally, it is the application of a point estimator to the data.
Formula
其中——
Where −
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${MLE}$ = Maximum Likelihood Estimation.
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${S}$ = Number of Success .
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${T}$ = Number of trials.
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${z}$ = Z-Critical Value.
Example
Problem Statement −
Problem Statement −
如果在 99% 置信区间水平上,在 9 次试验中掷硬币 4 次,那么该硬币的最佳成功点是多少?
If a coin is tossed 4 times out of nine trials in 99% confidence interval level, then what is the best point of success of that coin?
Solution −
Solution −
成功 (S) = 4 试验 (T) = 9 置信区间水平 (P) = 99% = 0.99。为了计算最佳点估计,让我们计算所有值 −
Success(S) = 4 Trials (T) = 9 Confidence Interval Level (P) = 99% = 0.99. In order to compute best point estimation, let compute all the values −
Step 1 -
Step 1 −
Step 2 -
Step 2 −
Step 3 -
Step 3 −
Step 4 -
Step 4 −
从 Z 表中求出 Z 临界值。Z 临界值 (z) = 对于 99% 水平 = 2.5758
Discover Z-Critical Value from Z table. Z-Critical Value (z) = for 99% level = 2.5758
Step 5 -
Step 5 −