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Residuals definitions

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  • Linear Regression

    Statistical method for modeling the relationship between a dependent variable and one or more independent variables using a straight line.
  • Least Squares Method

    Technique for finding the line of best fit by minimizing the sum of squared vertical distances between data points and the regression line.
  • Line of Best Fit

    Straight line that most closely represents the data in a scatterplot, determined by minimizing residuals.
  • Residual

    Vertical distance between an observed data point and its predicted value from the regression line, calculated as y minus ŷ.
  • Regression Equation

    Formula used to predict values of the dependent variable based on the independent variable, often written as ŷ = mx + b.
  • Predicted Value

    Estimated outcome for a given input, calculated using the regression equation and denoted as ŷ.
  • Observed Value

    Actual measured outcome in the dataset, represented as y in calculations.
  • Residual Plot

    Graph displaying residuals on the y-axis and original data values on the x-axis, used to assess model fit.
  • Random Pattern

    Arrangement of residuals without discernible structure, indicating a suitable regression model.
  • Discernible Pattern

    Visible structure in residuals, such as oscillation or divergence, suggesting the regression model is inadequate.
  • Oscillation

    Alternating up-and-down pattern in residuals, often resembling a wave, indicating poor linear fit.
  • Divergence

    Increasing spread of residuals as data progresses, implying non-constant variability and poor model fit.
  • Standard Deviation

    Measure of spread in residuals; non-constant values across data suggest issues with the regression model.
  • Dependent Variable

    Outcome being predicted in regression analysis, typically plotted on the y-axis.
  • Independent Variable

    Input or predictor in regression analysis, typically plotted on the x-axis.