Used tp predict the best line of fit by minimising the the distance of all data points to the line and minimises the sum of squared residuals.
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What doesthe slope of the line show?
How much the predicted Y score changes for each increment in X
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What does the intercept show?
The point where the regression line intersects the Y axis and is a predicted value of Y when X = 0
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What does Residual mean?
Basically means error; how far data point is from regression line and is the difference between actual Y score and the predicted Y.
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What does the standard model examine?
Unique contribution of all predictors on one criterion variable.
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What are the 6 assumptions of regression?
1. DV is measured on an interval scale 2. IV categorical data 3. No extreme multicolinearity between predictors 4. Residuals are normally distributed 5. Homoscedasticity 6. Linear relationships.
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What is multicolinearity?
Predictors shouldn't be extremely highly correlated.
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Other cards in this set
Card 2
Front
What is regression?
Back
Used tp predict the best line of fit by minimising the the distance of all data points to the line and minimises the sum of squared residuals.
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