Section 2.6 Flashcards

One quantitative variable: Regression Line Predicted Values Residuals Interpreting slope and intercept Cautions (8 cards)

1
Q

Regression Line

A

The straight line that best fits the data in a scatterplot

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2
Q

Estimated Equation of the Regression Line

A

y-hat = a+bx

(y-hat = predicted response)
(x = explanatory)

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3
Q

Observed Response Value

A

The response value observed for a particular data point

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4
Q

Predicted Response Value

A

The response value that would be predicted for a given X value, based on a model

(The best fitting line is that which makes the predicted values closest to the actual values)

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5
Q

Residual

A

The Residual for each data point is observed - predicted = y - y-hat

(The residual is also the vertical distance from each point to the line)

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6
Q

Least Square Line

A

The line which minimizes the sum of squared residuals

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7
Q

Slope

A

Increase in predicted y for every unit increase in X

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8
Q

Intercept

A

Predicted Y value when X = 0

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