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  2. 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.

  3. Scatter plot - Wikipedia

    en.wikipedia.org/wiki/Scatter_plot

    A plot located on the intersection of row and j th column is a plot of variables X i versus X j. [10] This means that each row and column is one dimension, and each cell plots a scatter plot of two dimensions. [citation needed] A generalized scatter plot matrix [11] offers a range of displays of paired combinations of categorical and ...

  4. Plot (graphics) - Wikipedia

    en.wikipedia.org/wiki/Plot_(graphics)

    A funnel plot is a scatterplot of treatment effect against a measure of study size. It is used primarily as a visual aid to detecting bias or systematic heterogeneity. Dot plot (statistics) : A dot chart or dot plot is a statistical chart consisting of group of data points plotted on a

  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. Variance function - Wikipedia

    en.wikipedia.org/wiki/Variance_function

    A scattor plot of years in the major league against salary (x$1000). The line is the trend in the mean. The plot demonstrates that the variance is not constant. The smoothed conditional variance against the smoothed conditional mean. The quadratic shape is indicative of the Gamma Distribution.

  7. Principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Principal_component_analysis

    Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.

  8. Variogram - Wikipedia

    en.wikipedia.org/wiki/Variogram

    Generally, plots show the semivariogram values as a function of sample point separation . In the case of empirical semivariogram, separation distance bins h ± δ {\displaystyle h\pm \delta } are used rather than exact distances, and usually isotropic conditions are assumed (i.e., that γ {\displaystyle \gamma } is only a function of h ...

  9. Deviance (statistics) - Wikipedia

    en.wikipedia.org/wiki/Deviance_(statistics)

    In statistics, deviance is a goodness-of-fit statistic for a statistical model; it is often used for statistical hypothesis testing.It is a generalization of the idea of using the sum of squares of residuals (SSR) in ordinary least squares to cases where model-fitting is achieved by maximum likelihood.