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  2. Scatterplot smoothing - Wikipedia

    en.wikipedia.org/wiki/Scatterplot_smoothing

    This line attempts to display the non-random component of the association between the variables in a 2D scatter plot. Smoothing attempts to separate the non-random behaviour in the data from the random fluctuations, removing or reducing these fluctuations, and allows prediction of the response based value of the explanatory variable .

  3. 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.

  4. 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.

  5. 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 ...

  6. Line fitting - Wikipedia

    en.wikipedia.org/wiki/Line_fitting

    Line fitting is the process of constructing a straight line that has the best fit to a series of data points. Several methods exist, considering: Vertical distance: Simple linear regression; Resistance to outliers: Robust simple linear regression

  7. Local regression - Wikipedia

    en.wikipedia.org/wiki/Local_regression

    Local regression or local polynomial regression, [1] also known as moving regression, [2] is a generalization of the moving average and polynomial regression. [3] Its most common methods, initially developed for scatterplot smoothing, are LOESS (locally estimated scatterplot smoothing) and LOWESS (locally weighted scatterplot smoothing), both pronounced / ˈ l oʊ ɛ s / LOH-ess.

  8. Fill-In (puzzle) - Wikipedia

    en.wikipedia.org/wiki/Fill-In_(puzzle)

    Raw "trial and error" is best used when only two or three words can potentially fit at a given location; temporarily assume one of the words, and see if an impossible letter combination results. If so, that word is not the one that should go in the grid at that location. [ 3 ]

  9. Log–log plot - Wikipedia

    en.wikipedia.org/wiki/Log–log_plot

    The left plot, titled 'Concave Line with Log-Normal Noise', displays a scatter plot of the observed data (y) against the independent variable (x). The red line represents the 'Median line', while the blue line is the 'Mean line'. This plot illustrates a dataset with a power-law relationship between the variables, represented by a concave line.