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  2. 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 .

  3. 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.

  4. Secondary plot (kinetics) - Wikipedia

    en.wikipedia.org/wiki/Secondary_plot_(kinetics)

    In enzyme kinetics, a secondary plot uses the intercept or slope from several Lineweaver–Burk plots to find additional kinetic constants. [1] [2]For example, when a set of v by [S] curves from an enzyme with a ping–pong mechanism (varying substrate A, fixed substrate B) are plotted in a Lineweaver–Burk plot, a set of parallel lines will be produced.

  5. Gran plot - Wikipedia

    en.wikipedia.org/wiki/Gran_plot

    The Gran plot is based on the Nernst equation which can be written as = + ⁡ {+} where E is a measured electrode potential, E 0 is a standard electrode potential, s is the slope, ideally equal to RT/nF, and {H +} is the activity of the hydrogen ion.

  6. Simple linear regression - Wikipedia

    en.wikipedia.org/wiki/Simple_linear_regression

    Deming regression (total least squares) also finds a line that fits a set of two-dimensional sample points, but (unlike ordinary least squares, least absolute deviations, and median slope regression) it is not really an instance of simple linear regression, because it does not separate the coordinates into one dependent and one independent ...

  7. Multilevel model - Wikipedia

    en.wikipedia.org/wiki/Multilevel_model

    and refer to the effect of the Level 2 predictor on the Level 1 intercept and slope respectively. u 0 j {\displaystyle u_{0j}} refers to the deviation in group j from the overall intercept. u 1 j {\displaystyle u_{1j}} refers to the deviation in group j from the average slope between the dependent variable and the Level 1 predictor.

  8. Linear interpolation - Wikipedia

    en.wikipedia.org/wiki/Linear_interpolation

    Linear interpolation on a data set (red points) consists of pieces of linear interpolants (blue lines). Linear interpolation on a set of data points (x 0, y 0), (x 1, y 1), ..., (x n, y n) is defined as piecewise linear, resulting from the concatenation of linear segment interpolants between each pair of data points.

  9. 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