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  2. Scatter matrix - Wikipedia

    en.wikipedia.org/wiki/Scatter_matrix

    For the notion in quantum mechanics, see scattering matrix. In multivariate statistics and probability theory, the scatter matrix is a statistic that is used to make estimates of the covariance matrix, for instance of the multivariate normal distribution.

  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. Pearson correlation coefficient - Wikipedia

    en.wikipedia.org/wiki/Pearson_correlation...

    Pearson's correlation coefficient is the covariance of the two variables divided by the product of their standard deviations. The form of the definition involves a "product moment", that is, the mean (the first moment about the origin) of the product of the mean-adjusted random variables; hence the modifier product-moment in the name.

  5. Estimation of covariance matrices - Wikipedia

    en.wikipedia.org/wiki/Estimation_of_covariance...

    The sample covariance matrix (SCM) is an unbiased and efficient estimator of the covariance matrix if the space of covariance matrices is viewed as an extrinsic convex cone in R p×p; however, measured using the intrinsic geometry of positive-definite matrices, the SCM is a biased and inefficient estimator. [1]

  6. 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.

  7. Homoscedasticity and heteroscedasticity - Wikipedia

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

    The disturbance in matrix A is homoscedastic; this is the simple case where OLS is the best linear unbiased estimator. The disturbances in matrices B and C are heteroscedastic. In matrix B, the variance is time-varying, increasing steadily across time; in matrix C, the variance depends on the value of . The disturbance in matrix D is ...

  8. Data and information visualization - Wikipedia

    en.wikipedia.org/wiki/Data_and_information...

    Scatter plots are often used to highlight the correlation between variables (x and y). Also called "dot plots" Scatter plot: Scatter plot (3D) position x; position y; position z; color; symbol; size; Similar to the 2-dimensional scatter plot above, the 3-dimensional scatter plot visualizes the relationship between typically 3 variables from a ...

  9. Biplot - Wikipedia

    en.wikipedia.org/wiki/Biplot

    The biplot is formed from two scatterplots that share a common set of axes and have a between-set scalar product interpretation. The first scatterplot is formed from the points (d 1 α u 1i, d 2 α u 2i), for i = 1,...,n. The second plot is formed from the points (d 1 1−α v 1j, d 2 1−α v 2j), for j = 1,...,p. This is the biplot formed by ...