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Related Concept Videos

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Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
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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.
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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.
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Collecting samples or responses from an entire population takes significant time and effort, so a researcher collects responses from only a sample of that population. Suppose a study needs to collect information about a specific mobile application. After sample collection, the researcher analyzes the data and discovers that most individuals in the sample use that specific mobile application. The sample proportion measures the number of individuals in a sample who either use or don't use the...
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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.
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Sample size calculation in clinical research.

Priya Ranganathan1, Vishal Deo2, C S Pramesh3

  • 1Department of Anaesthesiology, Tata Memorial Centre, Homi Bhabha National Institute, Mumbai, Maharashtra, India.

Perspectives in Clinical Research
|August 14, 2024
PubMed
Summary
This summary is machine-generated.

Calculating the right sample size is crucial for reliable and feasible research. This article explains the core principles for determining sample size in various study designs.

Keywords:
Epidemiologic methodsresearch designsample size

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Area of Science:

  • Biostatistics
  • Research Methodology

Background:

  • Sample size determination is fundamental to robust research design.
  • Inadequate sample sizes can compromise study reliability and feasibility.

Purpose of the Study:

  • To elucidate the principles of sample size calculation.
  • To guide researchers in selecting appropriate sample sizes for diverse study types.

Main Methods:

  • Review of fundamental statistical principles for sample size estimation.
  • Discussion of factors influencing sample size in different research designs.

Main Results:

  • Understanding key statistical concepts is vital for accurate sample size calculation.
  • The approach to sample size varies significantly across different research methodologies.

Conclusions:

  • Proper sample size calculation enhances research credibility and resource optimization.
  • Adherence to sample size principles ensures the validity and generalizability of study findings.