Data Analysis B

statisticsandprobability core

Data analysis B | NSW Curriculum Website

• MA5-DAT-C-02 displays and interprets datasets involving bivariate data

📖 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

Identify and describe numerical datasets involving 2 variables.pdf

• Distinguish between situations involving 1-variable and 2-variable (bivariate) data and explain when each is needed
• Explain the difference between variables that have an association and variables that have a causal relationship
• Identify and describe the independent variable and dependent variable in relationships with possible cause and effect

Represent datasets involving 2 numerical variables, using a scatter plot and a line of best fit, by eye.pdf

• Gather data on a topic of interest involving 2 numerical variables
• Represent the data using a scatter plot
• Create a line of best fit, by eye, on an existing scatter plot

Interpret data involving 2 numerical variables, using graphical representations.pdf

• Describe informally the association between 2 numerical variables and apply terminology about form (linear), strength (strong, moderate or weak) and direction (positive or negative)
• Use the line of best fit, by eye, to make predictions between known data values (interpolation) and what might happen beyond known data values (extrapolation)
• Explain the limitations of the model when making predictions