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相关概念视频

Estimating Population Standard Deviation01:26

Estimating Population Standard Deviation

3.0K
When the population standard deviation is unknown and the sample size is large, the sample standard deviation s is commonly used as a point estimate of σ. However, it can sometimes under or overestimate the population standard deviation. To overcome this drawback, confidence intervals are determined to estimate population parameters and eliminate any calculation bias accurately. However, this only applies to random samples from normally distributed populations. Knowing the sample mean and...
3.0K
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

4.0K
The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
4.0K
Estimating Population Mean with Known Standard Deviation01:16

Estimating Population Mean with Known Standard Deviation

8.3K
To construct a confidence interval for a single unknown population mean μ, where the population standard deviation is known, we need sample mean as an estimate for μ and we need the margin of error. Here, the margin of error (EBM) is called the error bound for a population mean (abbreviated EBM). The sample mean is the point estimate of the unknown population mean μ.
The confidence interval estimate will have the form as follows:
(point estimate - error bound, point estimate +...
8.3K
Estimating Population Mean with Unknown Standard Deviation01:22

Estimating Population Mean with Unknown Standard Deviation

7.6K
In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the...
7.6K
Sampling Distribution01:12

Sampling Distribution

12.3K
Given simple random samples of size n from a given population with a measured characteristic such as mean, proportion, or standard deviation for each sample, the probability distribution of all the measured characteristics is called a sampling distribution. How much the statistic varies from one sample to another is known as the sampling variability of a statistic. You typically measure the sampling variability of a statistic by its standard error. The standard error of the mean is an example...
12.3K
What are Estimates?01:06

What are Estimates?

5.0K
It isn't easy to measure a parameter such as the mean height or the mean weight of a population. So, we draw samples from the population and calculate the mean height or mean weight of the individuals in the sample. This sample data acts as a representative measure of the population parameter. These sample statistics are known as estimates. 
The estimate for the mean of a sample is denoted by ͞x, whereas the mean of the population is designated as μ. Further, parameters such...
5.0K

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相关实验视频

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Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
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Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

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记忆类型:在简单的随机抽样下,对人口变异的估计器的一般类型.

Anoop Kumar1, Anshika2, Walid Emam3

  • 1Department of Statistics, Central University of Haryana, Mahendergarh, Haryana, 123031, India.

Heliyon
|September 9, 2024
PubMed
概括

这项研究引入了简单随机抽样 (SRS) 中人口变化的新型记忆类型估计器. 这些估计器使用指数加权移动平均线 (EWMA),在模拟和真实世界数据分析中优于传统方法.

关键词:
62D05 这是一个很大的问题.效率表现效率表现的表现.指数加权移动平均线 (EWMA) 是指数加权的移动平均线.平均平方误差 (MSE) 是指基于记忆的方法 基于记忆的方法人口变异率的人口变异率简单的随机抽样.

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科学领域:

  • 统计 统计 统计 统计
  • 调查方法 调查方法
  • 统计推理 统计推理

背景情况:

  • 估计人口变化在统计调查中至关重要.
  • 传统的估计器可能无法充分利用时间数据.
  • 记忆类型的方法有可能提高调查的效率.

研究的目的:

  • 为简单随机抽样 (SRS) 中的人口变异提出一个新的类型的记忆类型估计器.
  • 评估拟议估计器的偏差和平均平方误差 (MSE).
  • 将新估计器的效率与现有方法进行比较.

主要方法:

  • 开发使用指数加权移动平均线 (EWMA) 的内存类型估计器.
  • 对偏差和平均平方误差 (MSE) 的分析表达式的推导.
  • 通过对假设人群和现实生活数据的模拟研究进行验证.

主要成果:

  • 建议的内存类型估计器与传统和其他内存类型估计器相比,显示出更高的效率.
  • 为新型估计器建立了理论效率条件.
  • 模拟和真实数据应用证实了拟议方法的实际优势.

结论:

  • 新型记忆类型估计器提供了一种更有效的方法来估计SRS.人口变异.
  • 基于EWMA的估计器有效地利用了当前和过去的调查信息.
  • 提出的方法为时间调查分析提供了宝贵的进步.