lesson
Distinguishing Correlation from Causation
Explain why correlation does not imply causation, identifying confounding and lurking variables in bivariate relationships.
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Bivariate Association: Covariance and Correlation Analysis
7 lessons
Goal
Quantify, interpret, and evaluate bivariate numerical associations using scatter plots, sample covariance, and Pearson's correlation coefficient.
7 lessons
0 of 7 done
- Constructing and Interpreting Scatter PlotsUp next
- Calculating and Interpreting Sample CovarianceNot started yet
- Calculating Pearson's Correlation Coefficient (r)Not started yet
- Properties and Interpretations of the Correlation CoefficientNot started yet
- Evaluating the Impact of Outliers on CorrelationNot started yet
- Understanding the Coefficient of Determination (r²)Not started yet
- Distinguishing Correlation from CausationYou are here
Learning standards covered
OGM.12.STA.1Open Global Math Standards 2026™ · 11th GradeCalculate and interpret measures of central tendency (mean, median, mode), position (percentiles, quartiles), dispersion (range, interquartile range, variance, standard deviation), and bivariate association (covariance, correlation); evaluate frequency distributions.
OGM.12.STA.3Open Global Math Standards 2026™ · 11th GradeDesign statistical experiments and random sampling methods; evaluate published statistical studies, media reports, and sample surveys; draw valid inferences and critique misleading statistical claims.