Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

4.1K
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...
4.1K
Choosing Between z and t Distribution01:25

Choosing Between z and t Distribution

2.8K
The z and the Student t distribution estimate the population mean using the sample mean and standard deviation. However, to decide which distribution to use for a calculation, one needs to determine the sample size, the nature of the distribution, and whether the population standard deviation is known. If the population standard deviation is known and the population is normally distributed, or if the sample size is greater than 30, the z distribution is preferred. The Student t distribution is...
2.8K
Estimating Population Mean with Unknown Standard Deviation01:22

Estimating Population Mean with Unknown Standard Deviation

7.7K
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...
7.7K
Random Sampling Method01:09

Random Sampling Method

11.1K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
11.1K
Stratified Sampling Method01:16

Stratified Sampling Method

12.0K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...
12.0K
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

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Exploring Spectral Graph Theory in Combinatorial Chemistry.

Combinatorial chemistry & high throughput screening·2026
Same author

Antibiotic Stewardship Program at a Tertiary Care Academic Hospital: A Comprehensive Analysis of an Audit Across Various Specialties.

Cureus·2026
Same author

AI-driven saliency-guided retinal vessel segmentation framework for sustainable digital pathology.

Frontiers in medicine·2026
Same author

Hydrothermal duck-feather keratin as a reagent-free bioreductant and capping matrix for bioactive silver nanoparticles.

Discover nano·2026
Same author

Simulation based new method for population variance using auxiliary information.

Scientific reports·2026
Same author

Retraction Note: Demystifying the association between economic development, transportation, tourism, renewable energy, and ecological footprint in Bay of Bengal Initiative for Multi-Sectoral Technical and Economic Cooperation region during globalization mode.

Environmental science and pollution research international·2026

相关实验视频

Updated: Jul 4, 2025

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.1K

在简单的随机抽样下,使用双重辅助信息改进了对人口分布函数的估计.

Sohaib Ahmad1, Sardar Hussain2, Aned Al Mutairi3

  • 1Department of Statistics, Abdul Wali Khan University, Mardan, Pakistan.

Heliyon
|February 1, 2024
PubMed
概括
此摘要是机器生成的。

本研究通过使用辅助信息,为人口分布函数引入了改进的统计估计器. 与现有技术相比,新方法显示出更高的准确性和效率.

关键词:
这是一个偏见的偏见.分布的功能是分配的功能.在MSE中,MSE是MSE.在此之前,先前前后.双重辅助信息是双重辅助信息.

更多相关视频

Sampling Soils in a Heterogeneous Research Plot
07:11

Sampling Soils in a Heterogeneous Research Plot

Published on: January 7, 2019

34.5K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

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

Published on: July 3, 2020

3.4K

相关实验视频

Last Updated: Jul 4, 2025

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans
09:23

Quantification of Information Encoded by Gene Expression Levels During Lifespan Modulation Under Broad-range Dietary Restriction in C. elegans

Published on: August 16, 2017

8.1K
Sampling Soils in a Heterogeneous Research Plot
07:11

Sampling Soils in a Heterogeneous Research Plot

Published on: January 7, 2019

34.5K
Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

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

Published on: July 3, 2020

3.4K

科学领域:

  • 统计 统计 统计 统计
  • 统计推理 统计推理
  • 调查抽样调查抽样

背景情况:

  • 在统计分析中,对人口分布函数 (DF) 的准确估计至关重要.
  • 当包含辅助信息时,现有的方法可能缺乏效率.
  • 简单的随机抽样是一种基本的技术,但需要改进.

研究的目的:

  • 为人口DF估计提出增强的估计器家族.
  • 在简单的随机抽样中利用双重辅助信息.
  • 为了提高分配函数估计的精度和效率.

主要方法:

  • 开发包含辅助变量的新型估计器家族.
  • 使用四个现实世界数据集进行经验验证.
  • 模拟研究,以评估估计器的性能和精度.

主要成果:

  • 拟议的估计器实现了最小平均平方误差 (MSE).
  • 与现有估计器相比,观察到相对效率 (PRE) 的提高.
  • 一个特定的推家庭在数据集中始终表现优于其他家庭.

结论:

  • 建议的估计器家族在估计人口分布函数方面提供了显著的改进.
  • 改进的方法在MSE和效率方面提供了卓越的性能.
  • 这些发现突出了在统计调查中提出的估计器的实际实用性.