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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. 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 ...

  4. Coefficient of determination - Wikipedia

    en.wikipedia.org/wiki/Coefficient_of_determination

    The sum of squares of residuals, also called the residual sum of squares: The total sum of squares (proportional to the variance of the data): The most general definition of the coefficient of determination is. In the best case, the modeled values exactly match the observed values, which results in and R2 = 1.

  5. Goodness of fit - Wikipedia

    en.wikipedia.org/wiki/Goodness_of_fit

    The goodness of fit of a statistical model describes how well it fits a set of observations. Measures of goodness of fit typically summarize the discrepancy between observed values and the values expected under the model in question. Such measures can be used in statistical hypothesis testing, e.g. to test for normality of residuals, to test ...

  6. Use a calculator to see how much you should spend per category based on your income — simply multiply your take-home pay by 0.50, 0.30 and 0.20 to understand how much you have for each of the ...

  7. Linear trend estimation - Wikipedia

    en.wikipedia.org/wiki/Linear_trend_estimation

    Linear trend estimation is a statistical technique used to analyze data patterns. Data patterns, or trends, occur when the information gathered tends to increase or decrease over time or is influenced by changes in an external factor. Linear trend estimation essentially creates a straight line on a graph of data that models the general ...

  8. Log–log plot - Wikipedia

    en.wikipedia.org/wiki/Log–log_plot

    Comparison of Linear, Concave, and Convex Functions\nIn original (left) and log10 (right) scales. In science and engineering, a log–log graph or log–log plot is a two-dimensional graph of numerical data that uses logarithmic scales on both the horizontal and vertical axes. Power functions – relationships of the form – appear as straight ...

  9. Linear least squares - Wikipedia

    en.wikipedia.org/wiki/Linear_least_squares

    Linear Template Fit (LTF) [7] combines a linear regression with (generalized) least squares in order to determine the best estimator. The Linear Template Fit addresses the frequent issue, when the residuals cannot be expressed analytically or are too time consuming to be evaluate repeatedly, as it is often the case in iterative minimization ...