Skip to main content
뒤로

Residuals definitions

컨트롤 버튼이 '내비게이션' 모드로 변경되었습니다.
1/15
  • 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.