Shared across all four courses, this content develops students' ability to analyse relationships between two quantitative variables. Pearson's product-moment correlation coefficient r is calculated using technology and interpreted in terms of the strength and direction of linear association, with the critical distinction between correlation and causation emphasised throughout. Students find and use the regression line of y on x for prediction, interpreting parameters in context. In AI, Spearman's rank correlation coefficient is also introduced as an alternative for non-linear monotonic relationships, and AI HL extends the treatment to non-linear regression models including quadratic, cubic, exponential and power forms, using the coefficient of determination R² to evaluate model fit.
Start here
Start by downloading the cheat sheet and the vocabulary below. After that, move to the video lessons with their respective exercise lists.
Video lessons
Learn the content with the videos provided and reinforce your comprehension by practicing with the exercise list above.
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