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  2. Log–log plot - Wikipedia

    en.wikipedia.org/wiki/Loglog_plot

    A loglog 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).

  3. Semi-log plot - Wikipedia

    en.wikipedia.org/wiki/Semi-log_plot

    On a semi-log plot the spacing of the scale on the y-axis (or x-axis) is proportional to the logarithm of the number, not the number itself. It is equivalent to converting the y values (or x values) to their log, and plotting the data on linear scales. A loglog plot uses the logarithmic scale for both axes, and hence is not a semi-log plot.

  4. File:S&P 500 Index Logarithmic Chart through Jan 2021.svg

    en.wikipedia.org/wiki/File:S&P_500_Index...

    English: S&P 500 Index Logarithmic Chart's Interesting Features. While S&P 500 data to linear plot scale is good for analysis of a span of 2 or 3 years, beyond that a logarithmic S&P 500 chart is best. This is because it gives the same Y or vertical displacement for a certain percentage move up or down regardless of date.

  5. Logarithmic scale - Wikipedia

    en.wikipedia.org/wiki/Logarithmic_scale

    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:

  6. Trend line (technical analysis) - Wikipedia

    en.wikipedia.org/wiki/Trend_line_(technical...

    For example, below is a chart of the S&P 500 since the earliest data point until April 2008. While the Oracle example above uses a linear scale of price changes, long term data is more often viewed as logarithmic: e.g. the changes are really an attempt to approximate percentage changes than pure numerical value.

  7. Linear trend estimation - Wikipedia

    en.wikipedia.org/wiki/Linear_trend_estimation

    All have the same trend, but more filtering leads to higher r 2 of fitted trend line. The least-squares fitting process produces a value, r-squared (r 2), which is 1 minus the ratio of the variance of the residuals to the variance of the dependent variable. It says what fraction of the variance of the data is explained by the fitted trend line.

  8. Detailed logarithmic timeline - Wikipedia

    en.wikipedia.org/wiki/Detailed_logarithmic_timeline

    Visual representation of the Logarithmic timeline in the scale of the universe. This timeline shows the whole history of the universe, the Earth, and mankind in one table. Each row is defined in years ago, that is, years before the present date, with the earliest times at the top of the chart. In each table cell on the right, references to ...

  9. Logarithmic growth - Wikipedia

    en.wikipedia.org/wiki/Logarithmic_growth

    Logarithmic growth is the inverse of exponential growth and is very slow. [2] A familiar example of logarithmic growth is a number, N, in positional notation, which grows as log b (N), where b is the base of the number system used, e.g. 10 for decimal arithmetic. [3] In more advanced mathematics, the partial sums of the harmonic series