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関連する概念動画

Transformations of Functions III01:20

Transformations of Functions III

131
Transformations modify the graphical representation of a function without changing its fundamental form. One common transformation is reflection, which flips the graph across a designated axis. When the vertical coordinates of all points are multiplied by the negative one, the entire graph is mirrored over the horizontal axis. This transformation reverses the vertical orientation of peaks and troughs, akin to signal inversion in electrical systems, where a waveform is flipped, but the timing of...
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Multiple Bar Graph01:07

Multiple Bar Graph

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As the name suggests, a multiple bar graph is the same as a bar graph but has multiple bars to depict relationships between different data values. One can include as many parameters as possible. However, each parameter must have the same unit of measurement.
Each bar or column in the multiple bar graph represents a data value. These graphs are used primarily in interrelating two or more sets of data. The categories of different kinds of data are listed along the horizontal or x-axis, whereas...
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Bar Graph01:07

Bar Graph

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A bar graph is also called a bar chart and consists of bars that are separated from each other. It either uses horizontal or vertical bars to show comparisons among categories. The bars can be rectangles, or they can be rectangular boxes (used in three-dimensional plots). One axis of the graph represents the specific categories being compared, and the other axis shows a discrete value. In this graph, the length of the bar for each category is proportional to the number or percent of individuals...
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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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Pie Chart01:04

Pie Chart

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A pie chart (or a pie graph) is a circular graphical chart or a pictorial representation of categorical data. It is divided into slices of pie each indicating numerical proportions. It is also used to show the relative sizes of data in a single chart.
In a pie chart, the central angle, the arc length of each slice, and the area are directly proportional to the quantity or percentage it represents. Some real-world examples that can be depicted using pie charts include marks obtained by students...
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Modified Boxplots00:57

Modified Boxplots

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A standard box and whisker plot informs us about the spread of the data in a given sample. One can identify the minimum value, maximum value, first quartile value, second quartile or median value, and third quartile.
However, the box plot does not tell the reader about outliers - values that lie far from the center of the data. We can modify the standard box and whisker plot to identify the outliers and visualize the actual spread of the data in a sample.
Initially, we calculate the adjusted...
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透明性を高めるためにデータビジュアライゼーションの変革

Tracey L Weissgerber1,2, Stacey J Winham3, Ethan P Heinzen3

  • 1Division of Nephrology and Hypertension (T.L.W., O.G.V., V.D.G., N.M.M.), Mayo Clinic, Rochester, MN.

Circulation
|October 29, 2019
PubMed
まとめ

多くの学術誌は連続データのためのバーグラフを推奨しないが,研究の約半数はまだそれを使用している. このガイドは,より明確な科学的なコミュニケーションのためのより良いデータ可視化技術を提供します.

キーワード:
バーグラフ基礎科学連続データデータ可視化

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科学分野:

  • 医学的な視覚化
  • 科学的コミュニケーション
  • データ表示

背景:

  • 雑誌は視覚化の問題により,連続データに対してバーグラフを使用しないことを推奨しています.
  • 既存の政策は,効果的なデータ表示の代替案について,限られた指針を提供している.
  • 最適でないデータ可視化手法が科学文献で広く使われている.

研究 の 目的:

  • 周周血管疾患のジャーナルにおけるデータ可視化方法を体系的に検討する.
  • 連続データに対するバーグラフの使用率を評価する.
  • 効果的なデータグラフィックの選択と作成に関するガイドラインを提供すること.

主な方法:

  • 主要な外周血管疾患誌の統計を体系的に検討する.
  • 連続したデータを表示するために使用される図型の分析.
  • 一般的なデータ可視化問題を特定する.

主要な成果:

  • 連続したデータを表示するために,バーグラフがデータ図の47.7%で使用されました.
  • 最適でないデータビジュアライゼーションの頻度が評価された.
  • バーグラフ以外にも共通する問題を特定しました.

結論:

  • 科学出版におけるデータ可視化に関する指針の改善が必要である.
  • ドットグラフ,ボックスグラフ,バイオリングラフなどの有効な代替手段を推進すべきです.
  • 作者はより情報的で正確な科学的な数字を作成するためにリソースと戦略を必要とします.