Difference between revisions of "S1 Correlation and Regression"
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*Scatter diagrams | *Scatter diagrams | ||
*Linear regression | *Linear regression | ||
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*Drawing regression line on a scatter diagram | *Drawing regression line on a scatter diagram | ||
*Explanatory (independent) and response (dependent) variables | *Explanatory (independent) and response (dependent) variables | ||
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== Preparation == | == Preparation == | ||
== Supporting activities == | == Supporting activities == | ||
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| + | === Regression === | ||
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| + | [[Media:Regression.ppt| Powerpoint Regression]] | ||
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| + | === Product Moment Correlation Coefficient === | ||
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| + | [[Media:Correlation_and_pmcc.ppt|Powerpoint PMCC]] | ||
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| + | [[Media:Correlation_worksheet.ppt|Worksheet PMCC (to use with the above Powerpoint)]] | ||
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== Consolidation == | == Consolidation == | ||
== Homework == | == Homework == | ||
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== Assessment == | == Assessment == | ||
== Notes == | == Notes == | ||
| + | Spec says "Calculation of the equation of a linear regression line using least squares" which we assume is a reference to understanding the component parts of the PMCC formula and being able to find them for small sets of data | ||
Latest revision as of 11:01, 11 July 2014
Part of S1
Contents
Objectives
- Scatter diagrams
- Linear regression
- Drawing regression line on a scatter diagram
- Explanatory (independent) and response (dependent) variables
- Applications and interpretations
- Make predictions within the range of values of the explanatory variable and recognise the dangers of extrapolation
- Variables other than x and y may be used
- Linear change of variable may be required
- The product moment correlation coefficient, its use, interpretation and limitations
Preparation
Supporting activities
Regression
Product Moment Correlation Coefficient
Worksheet PMCC (to use with the above Powerpoint)
Consolidation
Homework
Key questions
Assessment
Notes
Spec says "Calculation of the equation of a linear regression line using least squares" which we assume is a reference to understanding the component parts of the PMCC formula and being able to find them for small sets of data
