- MST-12-S2-08 analyses bivariate datasets using statistical processes
📖 Prior Knowledge
| Content | Prerequisite relationships |
|---|---|
| Linear Relationships | - Plot points on the Cartesian plane → Represent bivariate data with a scatter plot |
| Data Classification and Visualisation | - Define a statistical variable → Identify bivariate data |
| Linear Relationships B | - Interpret gradient–intercept form → Explain the effect of an outlier on a line of best fit - Find a line’s equation from its graph → Find the equation of a line of best fit |
| Data Analysis B | - Identify bivariate data (revisited content) - Identify independent and dependent variables (revisited content) - Represent bivariate data with a scatter plot (revisited content) - Draw a line of best fit (revisited content) - Describe association in bivariate data (revisited content) - Interpolate and extrapolate from a line of best fit (revisited content) - Explain the effect of an outlier on a line of best fit (revisited content) |
Bivariate datasets
- Distinguish between situations involving one variable data and bivariate data and explain when each is needed
- Explain the difference between variables that show correlation and those that have a causal relationship
- Identify the independent and dependent variables within a bivariate dataset where appropriate
- Analyse relationships between independent and dependent variables that may be described as causal
Scatter plots and lines of best fit
- Represent a bivariate dataset using a scatter plot
- Create a line of best fit on a scatter plot for a bivariate dataset, by eye and with digital tools
- Describe the form of a dataset as linear or non-linear based on the association between two variables
- Describe the strength of a linear relationship between two variables as strong, moderate or weak, and its direction as positive or negative
- Determine and interpret the intercept and gradient of the line of best fit from a given graph to form an equation of the line
- Calculate and interpret Pearson’s correlation coefficient () for a bivariate dataset using a scientific calculator to quantify the strength of a linear association between the two variables
- Determine the equation of the least-squares regression line for a bivariate dataset using a scientific calculator
- Use a spreadsheet to construct a scatter plot and the least-squares regression line for a bivariate dataset
- Examine lines of best fit to make predictions and recognise limitations of interpolation and extrapolation for bivariate datasets within a variety of contexts