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1/15IndietroSkip to main contentIndietroLinear 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.
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