Home · Unit 3 · Topic 1

Topic 1: Bivariate data analysis 1

Identifying and describing associations between two categorical variables

5 hours

• Understand the meaning of bivariate data.
• Construct two-way frequency tables and determine the associated row and column sums and percentages.
• Use an appropriately percentaged two-way frequency table to identify patterns that suggest the presence of an association. 1 interactive
• Understand an association in terms of differences observed in percentages across categories in a systematic and concise manner, and interpret this in the context of the data.

Identifying and describing associations between two numerical variables

6 hours

• Identify the explanatory variable and the response variable. 1 interactive
• Construct and use a scatterplot to identify the association between two numerical variables.
• Describe an association between two numerical variables in terms of direction (positive/negative), form (linear/non-linear) and strength (strong/moderate/weak). 1 interactive
• Calculate Pearson’s correlation coefficient,, from raw data using technology, and interpret it to quantify the strength of a linear association. 1 interactive
• Calculate the coefficient of determination, 2, from raw data using technology, and interpret it to assess the strength of a linear association in terms of the explained variation. 1 interactive
• Use the correlation coefficient,, to determine the coefficient of determination, 2, and vice versa.