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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.
A normal quantile plot for a simulated set of test statistics that have been standardized to be Z-scores under the null hypothesis. The departure of the upper tail of the distribution from the expected trend along the diagonal is due to the presence of substantially more large test statistic values than would be expected if all null hypotheses were true.
In mathematics, a function is a rule for taking an input (in the simplest case, a number or set of numbers) [5] and providing an output (which may also be a number). [5] A symbol that stands for an arbitrary input is called an independent variable, while a symbol that stands for an arbitrary output is called a dependent variable. [6]
The first intuitive approach (especially useful in less complex cases) is to analyze the relationship between each input and the output using scatter plots, and observe the behavior of these pairs. The diagrams give an initial idea of the correlation and which input has an impact on the output.
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 ...
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 .
This plot is colored such that those points having a fold-change less than 2 (log 2 = 1) are shown in gray. In statistics, a volcano plot is a type of scatter-plot that is used to quickly identify changes in large data sets composed of replicate data. [1] [2] It plots significance versus fold-change on the y and x axes
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 .