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Fitting Least-Squares Linear Regression Lines and Analyzing Residuals

Bivariate Data, Correlation, and Regression Modeling

9th Grade·Math·Open Global Math

Updated 1 month ago · 2 views

Determine the equation of the line of best fit and analyze residual plots to assess the appropriateness of a linear model.

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Bivariate Data, Correlation, and Regression Modeling

9th Grade · Math · Open Global Math

8 lessons

Goal

Analyze bivariate data, calculate and interpret Pearson's r, fit linear, quadratic, and exponential models, and evaluate predictions.

8 lessons

0 of 8 done

Bivariate Data: Scatter Diagrams and Linear CorrelationUp next
Calculating and Interpreting the Pearson Correlation CoefficientNot started yet
Distinguishing Correlation from Causation and Lurking VariablesNot started yet
Fitting Least-Squares Linear Regression Lines and Analyzing ResidualsYou are here
Making Predictions from Linear ModelsNot started yet
Identifying Linear, Quadratic, and Exponential Patterns in Scatter PlotsNot started yet
Fitting and Interpreting Quadratic Regression ModelsNot started yet
Fitting and Interpreting Exponential Regression ModelsNot started yet

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Learning standards covered

OGM.10.STP.3Open Global Math Standards 2026™ · 9th Grade

Construct scatter plots for bivariate numerical data, compute and interpret the Pearson correlation coefficient r, distinguish between association and causation, fit linear, quadratic, and exponential regression models, and make predictions.