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A stem-and-leaf display or stem-and-leaf plot is a device for presenting quantitative data in a graphical format, similar to a histogram, to assist in visualizing the shape of a distribution. They evolved from Arthur Bowley 's work in the early 1900s, and are useful tools in exploratory data analysis .
Stemplot : A stemplot (or stem-and-leaf plot), in statistics, is a device for presenting quantitative data in a graphical format, similar to a histogram, to assist in visualizing the shape of a distribution. They evolved from Arthur Bowley's work in the early 1900s, and are useful tools in exploratory data analysis.
Whereas statistics and data analysis procedures generally yield their output in numeric or tabular form, graphical techniques allow such results to be displayed in some sort of pictorial form. They include plots such as scatter plots , histograms , probability plots , spaghetti plots , residual plots, box plots , block plots and biplots .
Scatter plot (2D/3D) Stem-and-leaf plot; Parallel coordinates; Odds ratio; Targeted projection pursuit; Heat map; Bar chart; Horizon graph; Glyph-based visualization methods such as PhenoPlot [10] and Chernoff faces; Projection methods such as grand tour, guided tour and manual tour; Interactive versions of these plots; Dimensionality reduction ...
The most fundamental data analysis approaches are visualization (histograms, scatter plots, surface plots, tree maps, parallel coordinate plots, etc.), statistics (hypothesis test, regression, PCA, etc.), data mining (association mining, etc.), and machine learning methods (clustering, classification, decision trees, etc.). Among these ...
This is a list of statistical procedures which can be used for the analysis of categorical data, also known as data on the nominal scale and as categorical variables.
Scatter plot; Scatterplot smoothing; Scott's rule; Scree plot; Seasonal subseries plot; Self-similarity matrix; Semi-log plot; Sequence logo; Shewhart individuals control chart; Sina plot; Smoothing; Spaghetti plot; Spatial distribution; Stem-and-leaf display; Streamgraph; Sturges's rule
loglinear analysis (to identify relevant/important variables and possible confounders) Exact tests or bootstrapping (in case subgroups are small) Computation of new variables; Continuous variables Distribution Statistics (M, SD, variance, skewness, kurtosis) Stem-and-leaf displays; Box plots
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