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  2. Curve fitting - Wikipedia

    en.wikipedia.org/wiki/Curve_fitting

    Curve fitting[1][2] is the process of constructing a curve, or mathematical function, that has the best fit to a series of data points, [3] possibly subject to constraints. [4][5] Curve fitting can involve either interpolation, [6][7] where an exact fit to the data is required, or smoothing, [8][9] in which a "smooth" function is constructed ...

  3. Deming regression - Wikipedia

    en.wikipedia.org/wiki/Deming_regression

    In statistics, Deming regression, named after W. Edwards Deming, is an errors-in-variables model that tries to find the line of best fit for a two-dimensional data set. It differs from the simple linear regression in that it accounts for errors in observations on both the x - and the y - axis. It is a special case of total least squares, which ...

  4. Scatter plot - Wikipedia

    en.wikipedia.org/wiki/Scatter_plot

    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.

  5. Least squares - Wikipedia

    en.wikipedia.org/wiki/Least_squares

    The result of fitting a set of data points with a quadratic function Conic fitting a set of points using least-squares approximation. The method of least squares is a parameter estimation method in regression analysis based on minimizing the sum of the squares of the residuals (a residual being the difference between an observed value and the fitted value provided by a model) made in the ...

  6. Linear regression - Wikipedia

    en.wikipedia.org/wiki/Linear_regression

    t. e. In statistics, linear regression is a statistical model which estimates the linear relationship between a scalar response (dependent variable) and one or more explanatory variables (regressor or independent variable). The case of one explanatory variable is called simple linear regression; for more than one, the process is called multiple ...

  7. Bradford protein assay - Wikipedia

    en.wikipedia.org/wiki/Bradford_protein_assay

    First, add a line of best fit, or Linear regression and display the equation on the chart. Ideally, the R 2 value will be as close to 1 as possible. R represents the sum of the square values of the fit subtracted from each data point. Therefore, if R 2 is much less than one, consider redoing the experiment to get one with more reliable data ...

  8. Linear interpolation - Wikipedia

    en.wikipedia.org/wiki/Linear_interpolation

    Linear interpolation on a set of data points (x0, y0), (x1, y1), ..., (xn, yn) is defined as piecewise linear, resulting from the concatenation of linear segment interpolants between each pair of data points. This results in a continuous curve, with a discontinuous derivative (in general), thus of differentiability class .

  9. Scatterplot smoothing - Wikipedia

    en.wikipedia.org/wiki/Scatterplot_smoothing

    In statistics, several scatterplot smoothing methods are available to fit a function through the points of a scatterplot to best represent the relationship between the variables. Scatterplots may be smoothed by fitting a line to the data points in a diagram. This line attempts to display the non-random component of the association between the ...