Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Cluster Sampling Method01:20

Cluster Sampling Method

Appropriate sampling methods ensure 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 cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Sampling Plans01:23

Sampling Plans

Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Contaminants and Errors01:16

Contaminants and Errors

Effective sample preparation is crucial for accurate and reliable laboratory analysis. During this process, two significant sources of error can arise: concentration bias from improper sample splitting and contamination caused by methods used to reduce particle size, such as grinding or homogenization. Identifying and minimizing these potential errors is crucial to ensuring the validity of the analysis.
Another key consideration is determining the appropriate number of samples required to...
Margin of Error01:27

Margin of Error

The margin of error is also called the maximum error of an estimate. The margin of error is the maximum possible or expected difference between the observed sample parameter value and the actual population parameter value. For proportion, it is the maximum difference between the value of sample proportion obtained from the data and the true value of population proportion. As the true value of the population parameter is not known, the margin of error is calculated using the sample statistic.
Estimating Population Mean with Unknown Standard Deviation01:22

Estimating Population Mean with Unknown Standard Deviation

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 Guinness...
Estimating Population Standard Deviation01:26

Estimating Population Standard Deviation

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...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Association between physical activity and cancer risk among Chinese adults: a 10-year prospective study.

The international journal of behavioral nutrition and physical activity·2022
Same author

Cooking and future risk of all-cause and cardiopulmonary mortality.

Nature human behaviour·2022
Same author

Association between pneumonia hospitalisation and long-term risk of cardiovascular disease in Chinese adults: A prospective cohort study.

EClinicalMedicine·2022
Same author

Tobacco smoking and risks of more than 470 diseases in China: a prospective cohort study.

The Lancet. Public health·2022
Same author

MicroRNA profiling of different exercise interventions for alleviating skeletal muscle atrophy in naturally aging rats.

Journal of cachexia, sarcopenia and muscle·2022
Same author

Effectiveness of Multidomain Dormitory Environment and Roommate Intervention for Improving Sleep Quality of Medical College Students: A Cluster Randomised Controlled Trial in China.

International journal of environmental research and public health·2022
Same journal

[Research progress on the impact of the digital information environment on the health of children and adolescents].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2026
Same journal

[Exploration and practice of ideological and political education integration in the "One Core, Two Integrations" curriculum model for epidemiology].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2026
Same journal

[Progress in research of visualization of ideology and politics elements in curriculum and its importance for <i>Epidemiology</i> curriculum].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2026
Same journal

[Operation of WeChat official accounts of <i>Chinese Journal of Epidemiology</i>].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2026
Same journal

[Study on the risk factors of development for mild cognitive impairment to Alzheimer's disease based on the competitive risk joint model].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2026
Same journal

[Mendelian randomization study on related factors for esophageal adenocarcinoma and Barrett's esophagus].

Zhonghua liu xing bing xue za zhi = Zhonghua liuxingbingxue zazhi·2026
See all related articles

Related Experiment Video

Updated: Jul 1, 2026

Sampling Soils in a Heterogeneous Research Plot
07:11

Sampling Soils in a Heterogeneous Research Plot

Published on: January 7, 2019

[Estimation of sampling error on data from cluster sample survey].

Jun Lv1, Ping-ping He, Wen-xiao Tu

  • 1Department of Epidemiology & Biostatistics, School of Public Health, Peking University Health Science Center, Beijing 100083, China.

Zhonghua Liu Xing Bing Xue Za Zhi = Zhonghua Liuxingbingxue Zazhi
|September 13, 2008
PubMed
Summary
This summary is machine-generated.

Using incorrect statistical methods for cluster sample surveys can lead to underestimated sampling errors and flawed hypothesis testing. Proper analysis of complex survey data is essential for accurate results.

Related Experiment Videos

Last Updated: Jul 1, 2026

Sampling Soils in a Heterogeneous Research Plot
07:11

Sampling Soils in a Heterogeneous Research Plot

Published on: January 7, 2019

Area of Science:

  • Statistics
  • Survey Methodology

Context:

  • Cluster sample surveys are widely used for data collection.
  • Accurate estimation of sampling error is crucial for reliable statistical inference.

Purpose:

  • To highlight the importance of using appropriate statistical methods for cluster sample surveys.
  • To compare the impact of simple random sample (SRS) methods versus complex survey design methods on error estimation.

Summary:

  • Analysis of a two-stage cluster sample survey data revealed that standard error calculations assuming SRS often underestimate actual sampling error.
  • Improper statistical methods can lead to incorrect parameter estimation and erroneous hypothesis testing conclusions.
  • Specialized statistical methods and software for complex survey data are necessary for accurate analysis.

Impact:

  • Emphasizes the need for researchers to utilize appropriate statistical techniques for cluster sample survey data.
  • Promotes more reliable data interpretation and decision-making based on survey findings.
  • Contributes to the understanding of statistical best practices in survey research.