MYP 4Year 10Term 3
Bivariate Statistics
Scatter plots · Correlation · Line of best fit · Regression
Statistics
13 objectives
Learning objectives
What students should be able to do by the end of this unit.
Scatter Plots and Correlation
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- Identify the independent (explanatory) variable and the dependent (response) variable in a bivariate context.
- Construct a scatter plot from a bivariate data set, with appropriate scales and labels.
- Describe the form (linear / non-linear), direction (positive / negative) and strength (weak / moderate / strong) of a relationship.
- Distinguish between correlation and causation, and identify possible confounding variables.
- Interpret Pearson's correlation coefficient $r$ as a measure of the strength and direction of a linear relationship.
Line of Best Fit
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- Draw a line of best fit by eye through the mean point of the data.
- Use technology (GDC or spreadsheet) to find the equation of the least-squares regression line $y = mx + c$.
- Interpret the gradient and $y$-intercept of the regression line in the context of the data.
- Use the regression equation to make predictions (interpolation), and discuss the danger of extrapolation.
Residuals and Goodness of Fit (Extended)
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- Calculate the residual for a data point as $\text{observed} - \text{predicted}$.EXT
- Interpret the coefficient of determination $r^2$ as the proportion of variation explained by the model.EXT
- Compare $r$ and $r^2$ for different bivariate data sets and discuss which model fits best.EXT
- Discuss the limitations of a linear model when residuals show a clear pattern.EXT
Review pack
Curated revision materials parents and students can download.
A review pack for this unit is being prepared.