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Introduction to R01:11

Introduction to R

265
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...
265
Interpreting R Charts01:22

Interpreting R Charts

63
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...
63
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

125
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
125
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

364
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
364
The R Chart01:02

The R Chart

80
In statistical process control, control charts, particularly R charts, are instrumental in monitoring process variations and identifying non-random patterns that run charts might miss. R charts track the variability within process subgroups, which is crucial when standard deviation use is impractical or unknown process variations exist.
R charts are pivotal for pinpointing shifts in process variability. Stability is indicated when all data points remain within the defined upper and lower...
80
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

546
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
546

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相关实验视频

Updated: Jun 28, 2025

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
07:49

Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

Published on: April 18, 2025

157

一些使用R的教学资源,带有说明性示例,探索COVID-19数据.

Arthur Berg1, Nour Hawila1

  • 1Division of Biostatistics Penn State University Hershey Pennsylvania USA.

Teaching statistics
|April 12, 2024
PubMed
概括

这篇文章探讨了使用R用于数据科学教育,并根据种族分析了COVID-19死亡率. 它提供可重复的R代码,用于探索敏感的公共卫生数据.

科学领域:

  • 数据科学教育数据科学教育
  • 公共卫生研究 公共卫生研究
  • 生物统计学 生物统计学

背景情况:

  • 实施数据科学课程需要可访问的工具和相关的数据集.
  • 由于COVID-19大流行突显了健康差异,因此需要数据驱动的探索.
  • R是一个强大的,多功能工具,用于统计分析和数据可视化.

研究的目的:

  • 引导教育工作者使用R用于数据科学教学.
  • 展示R在分析COVID-19死亡率中的种族/种族差异中的应用.
  • 为教育和研究目的提供可复制的代码.

主要方法:

  • 在课程实施中使用R和R相关工具.
  • 应用R用于COVID-19死亡数据的探索性数据分析.
  • 利用R标记来进行可重复的图形和分析.

主要成果:

  • 通过可访问的资源,R促进了有效的数据科学教育.
  • 分析显示,与COVID-19死亡率相关的种族/种族分布.
  • 额外的R标记文件允许直接复制发现.

结论:

关键词:
在IDSSP中使用IDSSP.数据科学数据科学地图地图地图地图地图地图教学教学教学教学教学教学教学教学教学教学

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  • 对于数据科学教育和公共卫生研究来说,R是一个有价值的工具.
  • 使用R对COVID-19差异的数据探索可以告知有针对性的干预措施.
  • 教育材料应对大流行影响敏感地呈现.