Search results
Results from the WOW.Com Content Network
Graphs that are appropriate for bivariate analysis depend on the type of variable. For two continuous variables, a scatterplot is a common graph. When one variable is categorical and the other continuous, a box plot is common and when both are categorical a mosaic plot is common. These graphs are part of descriptive statistics.
For example, bivariate data on a scatter plot could be used to study the relationship between stride length and length of legs. In a bivariate correlation, outliers can be incredibly problematic when they involve both extreme scores on both variables.
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.
Whereas statistics and data analysis procedures generally yield their output in numeric or tabular form, graphical techniques allow such results to be displayed in some sort of pictorial form. They include plots such as scatter plots, histograms, probability plots, spaghetti plots, residual plots, box plots, block plots and biplots. [1]
Scatterplot : A scatter graph or scatter plot is a type of display using variables for a set of data. The data is displayed as a collection of points, each having the value of one variable determining the position on the horizontal axis and the value of the other variable determining the position on the vertical axis. [9]
Bivariate associations (correlations) Graphical techniques (scatter plots) It is important to take the measurement levels of the variables into account for the analyses, as special statistical techniques are available for each level: [132] Nominal and ordinal variables Frequency counts (numbers and percentages) Associations
The left plot, titled 'Concave Line with Log-Normal Noise', displays a scatter plot of the observed data (y) against the independent variable (x). The red line represents the 'Median line', while the blue line is the 'Mean line'. This plot illustrates a dataset with a power-law relationship between the variables, represented by a concave line.
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.