Lesson 18 Prediction and correlation

Predictions and correlation

Overview Resources
Worksheets 1 and 2
Pupils handle a correlation relationship in the form of a scatter of data - probably for the first time. The emphasis is on prediction, but within wide limits, with recognition of limits and estimates of likelihood.

In TM22: Comparing correlations, they will meet the idea that degrees of correlation can be compared quantitatively.
Aims Curriculum links
  • Correlation relations as distinguished from functional relations,
  • Intuitively approaching ‘line of best fit’.
  • Data handling: probability; median and range.
    Predicting data from a timed trend
    Pupils handle a set of incomplete data in a real-life setting of profits in a newly opened shop over a number of weeks, in table and graph form. They use a probabilistic pattern to think about missing data and possible versus likely values where only one variable is considered, They give reasons for their choices, taking into account their knowledge and what the data shows as a general trend which has variations. They then suggest ways to represent their intuitions on the graph.
    Predicting exam grades from each other
    Pupils handle a simple scatter graph showing a range in two variables representing pupils’ grades in maths and science. They make predictions, justify them by the patterns they observe, and approach the notion of a line of best fit, through it being meaningful for the best prediction, or the ‘least wrong!
    Additional notes
    Drawing conclusions from scatter diagrams, and a basic understanding of correlation is at GCSE grade 5. Drawing a line of best fit on a scatter diagram by inspection is at GCSE grade 6.

    Three Thinking Maths activities in this volume (TM18: Prediction and Correlation; TM22: Comparing correlations and TM24: Data relations) deal with correlation. TM22 continues by introducing the idea that the degree of correlation can be measured. TM24 involves both probability and correlation.


    Thinking Mathematics Lessons Copyright © by Michael Shayer and Mundher Adhami. All Rights Reserved.

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