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Year 12
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General Mathematics
Linear regression
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Conditions for linear modelling
1
Identify the explanatory and response variables
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2
Describe an association from a scatterplot
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3
Properties and assumptions of Pearson's r
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Least squares lines and residuals
4
Residuals and what least squares minimises
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5
Compute the least squares line from summary statistics
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6
Compute r and the least-squares line from data
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Regression models and prediction
7
Calculate and interpret the coefficient of determination
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8
Interpret the intercept and slope of a fitted model
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9
Predict from a fitted model: interpolation and extrapolation
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10
Construct and interpret a residual plot
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Residual plots and linearity
11
Construct and interpret a residual plot
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Regression analysis
12
A full bivariate investigation
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Chapter 2
Chapter 4