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Related Concept Videos

Histogram01:05

Histogram

15.8K
The histogram is a graphical representation in the x-y form of data distribution in a data set. The horizontal x-axis is labeled with what the data represents (for instance, distance from your home to school). The vertical y-axis is labeled either frequency or relative frequency (or percent frequency or probability).
A histogram graph consists of contiguous (adjoining) boxes. The heights of the bars correspond to frequency values. The graph will have the same shape with respective labels. The...
15.8K
Probability Histograms01:17

Probability Histograms

12.9K
A probability histogram is a visual representation of a probability distribution. Similar a typical histogram, the probability histogram consists of contiguous (adjoining) boxes. It has both a horizontal axis and a vertical axis. The horizontal axis is labeled with what the data represents. The vertical axis is labeled with probability. Each rectangular bar in the histogram is 1 unit wide, which suggests that the area under each bar equals the probability, P(x), where x is 1, 2, 3, and so on.
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Multiple Bar Graph01:07

Multiple Bar Graph

8.6K
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...
8.6K
Plotting of Topographic Maps01:29

Plotting of Topographic Maps

295
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,...
295
Modified Boxplots00:57

Modified Boxplots

10.6K
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...
10.6K
Relative Frequency Histogram01:14

Relative Frequency Histogram

6.1K
The relative frequency depicts the proportion of data points that have each value. The frequency tells the number of data points that have each value. Like the histogram, a relative frequency histogram also has the same shape with a horizontal scale (the x-axis), but the vertical scale (the y-axis) is marked with relative frequencies (percentages of the whole) instead of actual frequencies. A relative frequency histogram is a graphical representation of a frequency distribution where the...
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Polar Histogram Visualization of Acute Stress Disorder Scale Scores for Comprehensive Clinical Assessment
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Augmenting Parallel Coordinates Plots With Color-Coded Stacked Histograms.

Jinwook Bok, Bohyoung Kim, Jinwook Seo

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    This summary is machine-generated.

    Parallel Histogram Plot (PHP) enhances parallel coordinates plots (PCP) by adding color-coded histograms. This visualization technique effectively reveals attribute correlations, even for distant attributes, without clutter.

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    Area of Science:

    • Information Visualization
    • Computer Graphics
    • Data Analysis

    Background:

    • Parallel Coordinates Plot (PCP) suffers from clutter and scalability issues with large datasets.
    • Existing visualization techniques struggle to effectively display attribute relationships, especially for distant attributes.

    Purpose of the Study:

    • Introduce Parallel Histogram Plot (PHP) as an advancement over traditional PCP.
    • Address limitations of PCP by incorporating color-coded stacked-bar histograms.
    • Enable efficient visual examination of attribute correlations and data overviews.

    Main Methods:

    • Developed Parallel Histogram Plot (PHP) by integrating stacked-bar histograms with discrete color schemes into PCP.
    • Employed color-coding based on data ranking by a selected attribute for enhanced visual analysis.
    • Incorporated interactions like focus+context for efficient investigation of specific data regions.

    Main Results:

    • PHP effectively provides data overviews without clutter or scalability issues.
    • Color-coding facilitates visual examination of relationships between attributes, irrespective of axis proximity.
    • Controlled user study demonstrated consistent performance of PHP in estimating attribute correlations.

    Conclusions:

    • Parallel Histogram Plot (PHP) offers a scalable and effective solution for visualizing high-dimensional data.
    • PHP overcomes PCP limitations, enabling better understanding of attribute relationships and data distributions.
    • PHP shows significant potential for data analysis tasks requiring correlation estimation.