Empirical rule, or maybe the better way to remember the empirical rule is just the 68, 95, 99.7 rule.
经验法则,或者记住经验法则的更好方法就是 68、 95、 99. 7 法则。
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词汇 | Empirical Rule |
分类 | 英语词汇 英语翻译词典 |
释义 |
Empirical Rule
原声例句
可汗学院:统计学(视频版) Empirical rule, or maybe the better way to remember the empirical rule is just the 68, 95, 99.7 rule. 经验法则,或者记住经验法则的更好方法就是 68、 95、 99. 7 法则。 可汗学院:统计学(视频版) So this is another situation where we should use the empirical rule. 所以这是我们应该使用经验法则的另一种情况。 可汗学院:统计学(视频版) That's what the empirical rule tells us. 这就是经验法则告诉我们的。 可汗学院:统计学(视频版) So the empirical rule just gives us that answer. 所以经验法则正好给了我们这个答案。 可汗学院:统计学(视频版) So we can use the empirical rule. 所以我们可以使用经验法则。 可汗学院:统计学(视频版) So let's turn back to our empirical rule. 那么让我们回到我们的经验法则。 可汗学院:统计学(视频版) So how can we figure out that area under this normal distribution using the empirical rule? 那么我们如何使用经验法则计算出该正态分布下的区域呢? 可汗学院:统计学(视频版) Well we go from the empirical rule that 99.7% of the probability is within 3 standard deviations. 好吧,我们从经验法则出发,即 99.7% 的概率在 3 个标准差之内。 可汗学院:统计学(视频版) So if you just have to order things, you could have made that intuition, but it's good to do practice with the empirical rule. 因此,如果您只需要点菜,您可能会产生这种直觉, 但最好根据经验法则进行练习。 可汗学院:统计学(视频版) So the empirical rule tells us that this middle area between 1 standard deviation to the left and 1 standard deviation to the right, that right there is 68%. 所以经验法则告诉我们,这个中间区域在左边 1 个标准差和右边 1 个标准差之间,右边有 68%。 可汗学院:统计学(视频版) So let's see if we can use the empirical rule to answer this question, the area under the bell curve all the way up to 1, or everything to the left of 1. 那么让我们看看是否可以使用经验法则来回答这个问题,钟形曲线下的面积一直到 1, 或者 1 左边的所有区域。 可汗学院:统计学(视频版) The empirical rule tells us-- between two standard deviations, you have a 95% chance of getting bad results, or a 95% chance of getting a result that is within two standard deviations. 经验法则告诉我们——在两个标准差之间,你有 95% 的机会得到不好的结果, 或者有 95% 的机会得到一个在两个标准差范围内的结果。
英语百科
68–95–99.7 rule![]() ![]() In statistics, the 68–95–99.7 rule is a shorthand used to remember the percentage of values that lie within a band around the mean in a normal distribution with a width of one, two and three standard deviations, respectively; more accurately, 68.27%, 95.45% and 99.73% of the values lie within one, two and three standard deviations of the mean, respectively. In mathematical notation, these facts can be expressed as follows, where x is an observation from a normally distributed random variable, μ is the mean of the distribution, and σ is its standard deviation: |
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