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A log–log plot of y = x (blue), y = x 2 (green), and y = x 3 (red). Note the logarithmic scale markings on each of the axes, and that the log x and log y axes (where the logarithms are 0) are where x and y themselves are 1. Comparison of linear, concave, and convex functions when plotted using a linear scale (left) or a log scale (right).
A base-10 log scale is used for the Y-axis of the bottom left graph, and the Y-axis ranges from 0.1 to 1000. The top right graph uses a log-10 scale for just the X-axis, and the bottom right graph uses a log-10 scale for both the X axis and the Y-axis. Presentation of data on a logarithmic scale can be helpful when the data:
Such a diagram has pressure plotted on the vertical axis, with a logarithmic scale (thus the "log-P" part of the name), and the temperature plotted skewed, with isothermal lines at 45° to the plot (thus the "skew-T" part of the name). Plotting a hypothetical set of measurements with constant temperature for all altitudes would result in a line ...
The log–linear type of a semi-log graph, defined by a logarithmic scale on the y-axis (vertical), and a linear scale on the x-axis (horizontal). Plotted lines are: y = 10 x (red), y = x (green), y = log(x) (blue). The linear–log type of a semi-log graph, defined by a logarithmic scale on the x axis, and a linear scale on
A log-log chart spanning more than one order of magnitude along both axes: Semi-log or log-log (non-linear) charts x position; y position; symbol/glyph; color; connections; Represents data as lines or series of points spanning large ranges on one or both axes; One or both axes are represented using a non-linear logarithmic scale; Streamgraph
X-axis: The abundance rank. The most abundant species is given rank 1, the second most abundant is 2 and so on. Y-axis: The relative abundance. Usually measured on a log scale, this is a measure of a species abundance (e.g., the number of individuals) relative to the abundance of other species.
Semilog (log–linear) graphs use the logarithmic scale concept for visualization: one axis, typically the vertical one, is scaled logarithmically. For example, the chart at the right compresses the steep increase from 1 million to 1 trillion to the same space (on the vertical axis) as the increase from 1 to 1 million.
In probability theory, a log-normal (or lognormal) distribution is a continuous probability distribution of a random variable whose logarithm is normally distributed.Thus, if the random variable X is log-normally distributed, then Y = ln(X) has a normal distribution.