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  2. Spurious correlation of ratios - Wikipedia

    en.wikipedia.org/wiki/Spurious_correlation_of_ratios

    Form the proper fractions x/z and y/z for each triplet, and correlation will be found between these indices. The scatter plot above illustrates this example using 500 observations of x, y, and z. Variables x, y and z are drawn from normal distributions with means 10, 10, and 30, respectively, and standard deviations 1, 1, and 3 respectively, i.e.,

  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. Correlation - Wikipedia

    en.wikipedia.org/wiki/Correlation

    The adjacent image shows scatter plots of Anscombe's quartet, a set of four different pairs of variables created by Francis Anscombe. [23] The four variables have the same mean (7.5), variance (4.12), correlation (0.816) and regression line (= +). However, as can be seen on the plots, the distribution of the variables is very different.

  5. Correlogram - Wikipedia

    en.wikipedia.org/wiki/Correlogram

    For example, in time series analysis, a plot of the sample autocorrelations versus (the time lags) is an autocorrelogram. If cross-correlation is plotted, the result is called a cross-correlogram . The correlogram is a commonly used tool for checking randomness in a data set .

  6. Statistical graphics - Wikipedia

    en.wikipedia.org/wiki/Statistical_graphics

    Statistical graphics have been central to the development of science and date to the earliest attempts to analyse data. Many familiar forms, including bivariate plots, statistical maps, bar charts, and coordinate paper were used in the 18th century.

  7. Negative relationship - Wikipedia

    en.wikipedia.org/wiki/Negative_relationship

    Negative correlation can be seen geometrically when two normalized random vectors are viewed as points on a sphere, and the correlation between them is the cosine of the circular arc of separation of the points on a great circle of the sphere. [1] When this arc is more than a quarter-circle (θ > π/2), then the cosine is negative.

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