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相关概念视频

Interpreting R Charts01:22

Interpreting R Charts

68
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...
68
Introduction to R01:11

Introduction to R

345
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...
345
The R Chart01:02

The R Chart

84
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...
84
Scatter Plot01:15

Scatter Plot

6.9K
The most common and easiest way to display the relationship between two variables, x and y, is a scatter plot. A scatter plot shows the direction of a relationship between the variables. A clear direction happens when there is either:
6.9K
Plotting of Topographic Maps01:29

Plotting of Topographic Maps

48
Topographic maps represent the Earth's surface features using contour lines, which connect points of equal elevation to create a two-dimensional representation of three-dimensional terrain. Creating a topographic map requires a systematic approach.Begin by plotting a scaled grid and marking intersections corresponding to the survey's elevation data points. Assign elevation values at these intersections to build the base map. Next, determine contour levels using a consistent contour interval,...
48
Statgraphics01:10

Statgraphics

134
Statgraphics is a comprehensive statistical software suite designed for both basic and advanced data analysis. Originating in 1980 at Princeton University under Dr. Neil W. Polhemus, it was one of the pioneering tools for statistical computing on personal computers, with its public release in 1982 marking an early milestone in data science software. Over the years, it has evolved into a robust platform for data science, offering tools for regression analysis, ANOVA, multivariate statistics,...
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Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study
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SRplot:用于数据可视化和图形化的免费在线平台.

Doudou Tang1, Mingjie Chen2, Xinhua Huang3

  • 1Department of Respiratory and Critical Care Medicine, the Second Xiangya Hospital, Central South University, Changsha, Hunan, China.

PloS one
|November 9, 2023
PubMed
概括
此摘要是机器生成的。

SRplot是一个免费的,基于Web的工具,简化了科学出版物的数据可视化. 它提供了许多可通过用户友好的界面访问的图形功能,消除了对编程技能的需求.

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Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
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Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software
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Global and Current Research Trends of Single-Cell Sequencing in Cancer: A Bibliometric and Visualization Study

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190
Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
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Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

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Workflow for High-content, Individual Cell Quantification of Fluorescent Markers from Universal Microscope Data, Supported by Open Source Software
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科学领域:

  • 生物信息学是一种生物信息学.
  • 科学可视化科学可视化
  • 数据分析 数据分析

背景情况:

  • 科学出版物经常使用图形来总结数据.
  • 现有的图形工具往往需要编程技能,产生成本,或是特定于平台的.

研究的目的:

  • 介绍SRplot,一个免费访问,易于使用的用于生成科学图形的Web服务器.
  • 提供一个统一的平台,集成超过一百个常见的数据可视化和图形化功能.

主要方法:

  • SRplot是一个通过任何Web浏览器访问的Web服务器,需要最小的用户计算能力.
  • 具有用户友好的图形界面,可直接输入数据和实时生成图形.
  • 支持以出版质量的位图 (PNG,TIFF) 和矢量 (PDF,SVG) 格式下载图形.

主要成果:

  • SRplot集成了100多个数据可视化和图形化功能.
  • 通过直观的界面实时生成出版品质的图表.
  • 已在500多篇同行评审的出版物中使用,这表明广泛采用和实用性.

结论:

  • SRplot有效地解决了现有工具的局限性,为科学数据可视化提供了一个免费,可访问和多功能解决方案.
  • 基于用户反的持续更新确保SRplot仍然是研究人员的相关和改进资源.