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  2. ggplot2 - Wikipedia

    en.wikipedia.org/wiki/Ggplot2

    ggplot2 is an open-source data visualization package for the statistical programming language R.Created by Hadley Wickham in 2005, ggplot2 is an implementation of Leland Wilkinson's Grammar of Graphics—a general scheme for data visualization which breaks up graphs into semantic components such as scales and layers. ggplot2 can serve as a replacement for the base graphics in R and contains a ...

  3. Scatter plot - Wikipedia

    en.wikipedia.org/wiki/Scatter_plot

    A scatter plot, also called a scatterplot, scatter graph, scatter chart, scattergram, or scatter diagram, [2] is a type of plot or mathematical diagram using Cartesian coordinates to display values for typically two variables for a set of data. If the points are coded (color/shape/size), one additional variable can be displayed.

  4. Sina plot - Wikipedia

    en.wikipedia.org/wiki/Sina_plot

    A sina plot is a type of diagram in which numerical data are depicted by points distributed in such a way that the width of the point distribution is proportional to the kernel density. [ 1 ] [ 2 ] Sina plots are similar to violin plots , but while violin plots depict kernel density, sina plots depict the points themselves.

  5. Homoscedasticity and heteroscedasticity - Wikipedia

    en.wikipedia.org/wiki/Homoscedasticity_and...

    Plot with random data showing heteroscedasticity: The variance of the y-values of the dots increases with increasing values of x. In statistics , a sequence of random variables is homoscedastic ( / ˌ h oʊ m oʊ s k ə ˈ d æ s t ɪ k / ) if all its random variables have the same finite variance ; this is also known as homogeneity of variance .

  6. Scatterplot smoothing - Wikipedia

    en.wikipedia.org/wiki/Scatterplot_smoothing

    This line attempts to display the non-random component of the association between the variables in a 2D scatter plot. Smoothing attempts to separate the non-random behaviour in the data from the random fluctuations, removing or reducing these fluctuations, and allows prediction of the response based value of the explanatory variable .

  7. Identity line - Wikipedia

    en.wikipedia.org/wiki/Identity_line

    In this case, the plotted points are quantiles, making it a Q–Q plot. The Keynesian cross diagram includes an identity line to show states in which aggregate demand equals output In a 2-dimensional Cartesian coordinate system , with x representing the abscissa and y the ordinate , the identity line [ 1 ] [ 2 ] or line of equality [ 3 ] is the ...

  8. Partial regression plot - Wikipedia

    en.wikipedia.org/wiki/Partial_regression_plot

    The influences of individual data values on the estimation of a coefficient are easy to see in this plot. It is easy to see many kinds of failures of the model or violations of the underlying assumptions (nonlinearity, heteroscedasticity, unusual patterns). . Partial regression plots are related to, but distinct from, partial residual plots.

  9. UpSet plot - Wikipedia

    en.wikipedia.org/wiki/UpSet_plot

    UpSet plots are related to Mosaic Plots, although Mosaic plots are designed for categorical instead of set data. UpSet plots became popular as they became available as an R -library based on ggplot2 , [ 3 ] and were subsequently re-implemented in various programming languages, such as Python , and others. [ 4 ]