2025年clt框架_中心极限定理clt数据科学

大家好，我是讯享网，很高兴认识大家。

clt框架

As we have seen in the previous article, “Inferential Statistics” plays a significant role in Data Science. Central Limit Theorem(CLT) is the most commonly used technique by Data Scientists in the real-world, a part of Inferential Statistics.

正如我们在上一篇文章中所见，“ 推理统计 ”在数据科学中起着重要作用。中心极限定理(CLT)是数据科学家在现实世界中最常用的技术，它是推理统计的一部分。

To know about CLT, first, we need to understand the following topics:

要了解CLT，首先，我们需要了解以下主题：

Sample
样品
Sampling Distribution
抽样分布

1.样品 (1. Sample)

The selection of some of the employees/population from the whole employees/population list is known as Sample.

从整个雇员/人口列表中选择一些雇员/人口称为Sample 。

Let’s say we have a company in which 30,000 employees are working. We want to find out the daily commute time of all the employees. It will be very tedious and time-consuming to go to every employee and note their commute time.

假设我们有一家拥有30,000名员工的公司。我们想找出所有员工的每日通勤时间。拜访每个员工并记录他们的通勤时间将是非常繁琐且耗时的。

Let’s see if there is another way to complete the task. Say in the company; we took a survey of 100 random employees. After the survey, we calculated the mean of the employees’ commute time at 36.6 min. Is this enough to say that all the employee’s commute time is 36.6 min by considering just 100 random employees?

让我们看看是否有另一种方式来完成任务。在公司说；我们对100名随机雇员进行了调查。调查后，我们计算出员工上下班时间的平均值为36.6分钟。这是否足以说明仅考虑100名随机雇员，所有雇员的通勤时间为36.6分钟？

No, we cannot say that. The overall mean will be something of 36.6+error, i.e., if the error is 3 min, then the employees’ overall mean will be between “36.6–3” to “36.6+3”. Now, how do we find out the error?

不，我们不能这么说。总体平均误差为36.6+ 误差，即，如果误差为3分钟 ，则员工的总体平均误差将在“ 36.6–3 ”至“ 36.6 + 3 ”之间。现在，我们如何找出错误？

To answer that question, first, we have to understand the Sampling Terminology.

要回答这个问题，首先，我们必须了解采样术语。

讯享网

Total number of items/population, Population Size = N
项目/总人口数，人口总数= N
Mean of the population, Population Mean(μ) = (Σ * X)/N
总体平均值，总体平均值(μ)=(Σ* X)/ N
Variance of the population, Population Variance(σ²) = Σ( Xi — μ )²/ N
人口方差 ， 人口方差(σ²)=Σ(Xi —μ)²/ N
Number of items/population, Sample Size = n
项目/人口数量，样本数量= n
Mean of the sample employees, Sample Mean(x¯) = (Σ * x)/n
样本员工的均值， 样本均值(x¯) = (Σ* x)/ n
Variance of the sample, Sample Variance(S²) = Σ( xi — x¯)²/ n-1
样本方差 ， 样本方差(S²)=Σ(xi-x¯)²/ n-1

Let’s see how we can find the Sample Mean & Sample Variance from a given Sample Size,

让我们看看如何从给定的样本量中找到样本均值和样本方差，

We need to find the average height of people in an area from the following sample data.

我们需要从以下样本数据中找到一个区域中人的平均身高。

2025年clt框架_中心极限定理clt数据科学

1.样品 (1. Sample)

相关推荐