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  2. Log–log plot - Wikipedia

    en.wikipedia.org/wiki/Log–log_plot

    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).

  3. Linear function (calculus) - Wikipedia

    en.wikipedia.org/wiki/Linear_function_(calculus)

    The simplest is the slope-intercept form: = +, from which one can immediately see the slope a and the initial value () =, which is the y-intercept of the graph = (). Given a slope a and one known value () =, we write the point-slope form:

  4. Slope - Wikipedia

    en.wikipedia.org/wiki/Slope

    Slope illustrated for y = (3/2)x − 1.Click on to enlarge Slope of a line in coordinates system, from f(x) = −12x + 2 to f(x) = 12x + 2. The slope of a line in the plane containing the x and y axes is generally represented by the letter m, [5] and is defined as the change in the y coordinate divided by the corresponding change in the x coordinate, between two distinct points on the line.

  5. Linear equation - Wikipedia

    en.wikipedia.org/wiki/Linear_equation

    A non-vertical line can be defined by its slope m, and its y-intercept y 0 (the y coordinate of its intersection with the y-axis). In this case, its linear equation can be written = +. If, moreover, the line is not horizontal, it can be defined by its slope and its x-intercept x 0. In this case, its equation can be written

  6. Semi-log plot - Wikipedia

    en.wikipedia.org/wiki/Semi-log_plot

    The naming is output–input (y–x), the opposite order from (x, y). 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

  7. Simple linear regression - Wikipedia

    en.wikipedia.org/wiki/Simple_linear_regression

    In this case, the slope of the fitted line is equal to the correlation between y and x corrected by the ratio of standard deviations of these variables. The intercept of the fitted line is such that the line passes through the center of mass (x, y) of the data points.

  8. Y-intercept - Wikipedia

    en.wikipedia.org/wiki/Y-intercept

    Functions of the form = have at most one -intercept, but may contain multiple -intercepts. The x {\displaystyle x} -intercepts of functions, if any exist, are often more difficult to locate than the y {\displaystyle y} -intercept, as finding the y {\displaystyle y} -intercept involves simply evaluating the function at x = 0 {\displaystyle x=0} .

  9. Arrhenius plot - Wikipedia

    en.wikipedia.org/wiki/Arrhenius_plot

    When plotted in the manner described above, the value of the y-intercept (at = / =) will correspond to ⁡ (), and the slope of the line will be equal to /. The values of y-intercept and slope can be determined from the experimental points using simple linear regression with a spreadsheet .