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Residuals definitions
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Define:
Linear Regression
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Linear Regression
A statistical method that finds the line minimizing the sum of squared vertical distances from data points.
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Terms in this set (15)
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Linear Regression
A statistical method that finds the line minimizing the sum of squared vertical distances from data points.
Least Squares Method
A technique that determines the best-fitting line by minimizing the sum of squared residuals.
Line of Best Fit
A straight line that most closely approximates the data in a scatterplot, based on minimizing residuals.
Residual
The vertical distance between an observed value and its predicted value from the regression line.
Residual Plot
A graph displaying residuals on the y-axis and original x-values on the x-axis to assess model fit.
Regression Equation
A formula used to calculate predicted values for y based on given x values in linear regression.
Predicted Value
The y-value estimated from the regression equation for a specific x-value, often denoted as ŷ.
Observed Value
The actual y-value from the dataset corresponding to a specific x-value.
Random Pattern
A distribution of residuals with no discernible structure, indicating a good model fit.
Discernible Pattern
A recognizable structure in residuals, such as oscillation or divergence, suggesting a poor model fit.
Standard Deviation
A measure of spread in residuals; non-constant values across data suggest model inadequacy.
Divergence
A situation where residuals become increasingly spread out, indicating changing variability in the data.
Oscillation
A pattern in residuals where values alternate above and below the axis, often resembling a wave.
Y-Axis
The vertical axis on a graph, used for plotting residuals in a residual plot.
X-Axis
The horizontal axis on a graph, representing the original data values in a residual plot.