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	5.2 The MLR Model and Estimated Model (Edgewood College School of Business) View
	Checking Linear Regression Assumptions in R \| R Tutorial 5.2 \| MarinStatsLectures (MarinStatsLectures-R Programming \u0026 Statistics) View
	Applied Regression Modeling 5.2e: Multiple linear reg. - overfitting, extrapolation, missing data (Iain's Math \u0026 Stat Screencasts) View
	Applied Regression Modeling 5.2a: Multiple linear regression pitfalls - nonconstant variance (Iain's Math \u0026 Stat Screencasts) View
	Applied Regression Modeling 5.2c: Multiple linear regression pitfalls - multicollinearity (Iain's Math \u0026 Stat Screencasts) View
	Simple Linear Regression: Checking Assumptions with Residual Plots (jbstatistics) View
	Applied Regression Modeling 5.2b: Multiple linear regression pitfalls - autocorrelation (Iain's Math \u0026 Stat Screencasts) View
	Applied Regression Modeling 5.2d: Multiple linear regression pitfalls - Simpson's paradox (Iain's Math \u0026 Stat Screencasts) View
	5.2. Coefficient of determination and correlation (Lazarski Open Courses) View
	Checking assumptions of the linear model (Drew Tyre) View