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相关概念视频

Stratified Sampling Method01:16

Stratified Sampling Method

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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...
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Introduction to R01:11

Introduction to R

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R is a powerful software environment for statistical computing and graphics. Originating as an implementation of the S language, developed at Bell Laboratories, R has evolved into a robust, open-source statistical software favored by statisticians and data scientists worldwide. Its comprehensive suite includes data manipulation, calculation, and graphical display capabilities, making it versatile for data analysis and visualization. Its programming language is at the core of R's...
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Statistical Analysis System (SAS)01:14

Statistical Analysis System (SAS)

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SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
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Interpreting R Charts01:22

Interpreting R Charts

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R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum...
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One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

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This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
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相关实验视频

Updated: Jul 11, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
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在R中使用STRAND建模动物网络数据.

Cody T Ross1, Richard McElreath1, Daniel Redhead1

  • 1Department of Human Behavior, Ecology, and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany.

The Journal of animal ecology
|November 8, 2023
PubMed
概括
此摘要是机器生成的。

本研究介绍了STRAND,这是一个简化动物社会网络分析生成网络模型的R包. 它使研究人员能够轻松地将先进的贝叶斯模型应用于各种社会数据.

关键词:
R 软件 软件 软件 软件 软件动物网络动物网络生成型模型是一种生成型模型.社交网络 社交网络社会关系社会关系.

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科学领域:

  • 生态生态学 生态生态学
  • 网络科学 网络科学
  • 计算生物学 计算生物学

背景情况:

  • 在社交网络分析中,日益需要生成模型.
  • 由于软件有限,对实地研究人员等最终用户来说,实施这些模型是具有挑战性的.
  • 现有的方法往往比基于 permutation 的方法更难获得.

研究的目的:

  • 引入STRAND R包,用于可访问的生成网络建模.
  • 为动物社交网络数据的贝叶斯分析提供一个用户友好的工具.
  • 展示生成模型对各种网络数据类型的应用.

主要方法:

  • 开发了STRAND R套件的开发工作.
  • 实现生成模型,包括随机区块模型和社会关系模型.
  • 使用简单的基础R语法,以方便应用.
  • 提供一个模拟比例,数量或二进制网络数据的教程.

主要成果:

  • 斯特兰提供了一套用于贝叶斯分析动物社交网络数据的生成模型.
  • 该软件包支持各种数据类型 (比例,计数,二进制) 和建模框架.
  • 对于典型的最终用户来说,STRAND简化了复杂网络模型的应用.

结论:

  • STRAND显著降低了在动物行为研究中应用生成网络模型的进入壁垒.
  • 该套件有助于在社交网络分析中更广泛地使用先进的分析技术.
  • STRAND提高了现场研究人员和生态学家对复杂建模的可访问性.