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Hint

1

R²

R²% of the response variable is accounted for by our linear model

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2

Slope: b or b1

Our model predicts the response variable will (increase/decrease) units, on average, for every extra unit of the explanatory variable

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3

Intercept

Our model predicts “a” units on average of the response variable when we have 0 units of the explanatory variable

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4

how to analyze a residuals plot

is the association random?

does the residuals plot display a fairly even spread?

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5

what does not verify a linear model?

R²

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6

as R² goes up…

the better the LSRL will predict ‘y’ for a given ‘x’

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7

what is a residual?

actual y - predicted y

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8

what do you need to say to describe an association

context, units, direction, strength, form (linear, curved), unusual features, SENTENCE OF ASSOCIATION

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9

purpose of correlation: ‘r’

gives direction (sign) and a measure of strength/more objective measure of strength

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10

properties of ‘r’

r is dimensionless, sign of r gives direction, value of r will always lie -1<r<1, non-resistant, LTs do not affect r (but reexpressions do), not affected by which variable on which axis

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11

Standard deviation

The actual values of the response variable vary from our model’s predicted values (with a standard deviation of ____ units) or (with an average deviations of _____ units)

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