Illustrating the distribution of data is necessary to understand patterns, variability within datasets and some data characteristics like outliers. Some very common distribution charts include histograms, box plots, and density plots. These visualizations are useful in exploratory analyses as well as data reporting.
Usage Notes: Box and Whisker plots are used to summarize descriptive statistics. The small horizontal lines (whiskers) at the extreme ends of the plot are the min and max values. The box represents the interquartile range of the dataset with the lower hinge (bottom edge) of the box showing the first quartile and the upper hinge showing the 75% quartile. The line in the middle of the box represents the median and outliers are indicated by dots above or below the whiskers.
Also see: Violin chart
Usage Notes: Bubble charts are a type of scatter plot used to compare three dimensional data. Two values are represented by the x and y and a third value is represented by a dot of varying size representing the magnitude of the z-value.
Also see: Scatterplot, dot density map.
Usage Notes : Density plots are used to visualize the distribution of continuous data, and are good for showing distribution characteristics, such as shape, central tendency, and spread, making them valuable for understanding data patterns and comparing distributions. Density plots are preferable to other chart types, such as bar charts, when dealing with continuous variables, as they provide a smooth, continuous representation of data without requiring data discretization. They are particularly useful for detecting outliers, identifying bimodal or multimodal distributions, and exploring data before more advanced analysis.
See also: Histogram
Usage Notes : Dot matrix charts display categorical or binary data in a grid of dots, illustrating frequencies or patterns across dimensions. They are useful for showing precise counts and are preferred over other charts when dealing with binary or grid-based data representation, offering a compact, visually informative way to convey categorical relationships.
Usage Notes : Histograms are used to visualize the distribution of continuous data by grouping it into intervals (bins) and representing the frequency or density of data points within each bin. They are effective for revealing data patterns, central tendencies, and variations. Histograms are preferable to other chart types, such as bar charts, when dealing with continuous data as they provide a continuous representation without data discretization. They are particularly useful for identifying data skewness, modality, and outliers, making them a valuable tool in statistical analysis and data exploration.
See also : Bar Chart, Density plot
Usage Notes : Multi-set bar charts are used to compare the distribution of categorical data across multiple data sets or categories. They are useful for visualizing how the distribution of data varies across different sets or groups. This makes them preferable to other chart types when the focus is on understanding the distribution of categorical data and identifying patterns or variations in the data's spread among different categories or sets.
See also : Bar Chart, Density plot
Usage Notes : Pictogram charts are used to represent quantities or proportions with pictures or icons. They are effective for conveying data in a visually engaging and easily understandable manner, especially when dealing with simple, categorical data or making data more accessible to a broad audience. Pictogram charts can be preferable to other chart types for visualization when the primary goal is to communicate data distribution in a highly intuitive and memorable way, making them valuable in educational materials, infographics, and presentations where clarity and accessibility are paramount.
See also : Bar Chart
Usage Notes : Stem and leaf plots are used for summarizing the distribution of numerical data while retaining individual data points. They are useful for showing the spread and clustering of data values, making them effective in exploratory data analysis and statistics. The stem represents the 10s number and the leaf represents the ones and each number in the leaf represents a distinct observation. Stem and Leaf Plots are gnereally useful for small numbers and can become impractical for larger observations. Stem and leaf plots are preferable to other chart types when you need to maintain the granularity of data while visualizing its distribution, providing insights into data patterns, outliers, and central tendencies in a straightforward and compact manner.
See also : Bar Chart, Histogram
.
Usage Notes : Tally charts are among the most basic visualization techniques and are typically not used in scholarly communication, but can be used effectively in visualizations that engage the public.
Source: https://www.morgan.edu/about/our-history
