Standard Statistical analysis - Bivariate data analysis

This lesson comprises two (2) master classes focusing on:

• Bivariate scatter plots
• Lines of best fit
• Pearson's correlation coefficient
• Describing bivariate data sets
• Limitations of interpolation and extrapolation

Content:

MS-S4

• Construct a bivariate scatterplot to identify patterns in the data that suggest the presence of an association
• Use bivariate scatterplots (constructing them when needed) to describe the patterns, features and associations of bivariate datasets, justifying any conclusions
  • describe bivariate datasets in terms of form (linear/non-linear) and, in the case of linear, the direction (positive/negative) and strength of any association (strong/moderate/weak)
  • identify the dependent and independent variables within bivariate datasets where appropriate
  • describe and interpret a variety of bivariate datasets involving two numerical variables using real-world examples from the media or freely available from government or business datasets
  • calculate and interpret Pearson’s correlation coefficient (r) using technology to quantify the strength of a linear association of a sample
• Model a linear relationship by fitting an appropriate line of best fit to a scatterplot and using it to describe and quantify associations
  • fit a line of best fit both by eye and by using technology to the data
  • fit a least-squares regression line to the data using technology
  • interpret the intercept and gradient of the fitted line
• Use the appropriate line of best fit, both found by eye and by applying the equation, to make predictions by either interpolation or extrapolation
  • recognise the limitations of interpolation and extrapolation, and interpolate from plotted data to make predictions where appropriate
• Solve problems that involve identifying, analysing and describing associations between two numerical variables
• Construct, interpret and analyse scatterplots for bivariate numerical data in practical contexts
  • demonstrate an awareness of issues of privacy and bias, ethics, and responsiveness to diverse groups and cultures when collecting and using data
  • investigate using biometric data obtained by measuring the body or by accessing published data from sources including government organisations, and determine if any associations exist between identified variables