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  2. Rug plot - Wikipedia

    en.wikipedia.org/wiki/Rug_plot

    Download QR code; Print/export Download as PDF; Printable version; ... Rug plots in Matlab; Rug plots in Python using the Seaborn library This page was ...

  3. A beginner’s guide to data visualization with Python and Seaborn

    www.aol.com/beginner-guide-data-visualization...

    Data visualization is a technique that allows data scientists to convert raw data into charts and plots that generate valuable insights. There are many tools to perform data visualization, such as ...

  4. Matplotlib - Wikipedia

    en.wikipedia.org/wiki/Matplotlib

    Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy. It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter , wxPython , Qt , or GTK .

  5. 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 ...

  6. MATLAB - Wikipedia

    en.wikipedia.org/wiki/MATLAB

    MATLAB (an abbreviation of "MATrix LABoratory" [18]) is a proprietary multi-paradigm programming language and numeric computing environment developed by MathWorks.MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages.

  7. Generalization error - Wikipedia

    en.wikipedia.org/wiki/Generalization_error

    Main page; Contents; Current events; Random article; About Wikipedia; Contact us

  8. Standard error - Wikipedia

    en.wikipedia.org/wiki/Standard_error

    For a value that is sampled with an unbiased normally distributed error, the above depicts the proportion of samples that would fall between 0, 1, 2, and 3 standard deviations above and below the actual value.

  9. Homoscedasticity and heteroscedasticity - Wikipedia

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

    [1] [2] [3] Assuming a variable is homoscedastic when in reality it is heteroscedastic (/ ˌ h ɛ t ər oʊ s k ə ˈ d æ s t ɪ k /) results in unbiased but inefficient point estimates and in biased estimates of standard errors, and may result in overestimating the goodness of fit as measured by the Pearson coefficient.