Module 1.1 Intro to Linear Regression Flashcards

1
Q

measure of strength of the linear relationship between two variables

A

correlation coefficient (r)

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2
Q

has no unit of measurement

A

r (correlation coefficient)

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3
Q

r (correlation coefficient) =

A

covariance of X and Y/(std dev of X)*(std dev of Y)

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4
Q

what is correlation coefficient bounded by

A

1 and -1

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5
Q

slope coefficient (b-hat 1) =

A

covariance of X and Y/variance of X

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6
Q

represents the value of the dependent variable at the point of intersection of the regression line and the axis of the dependent variable

A

estimated intercept (b-hat 0)

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7
Q

occurs when variance of residuals differ across observations

A

heteroskedasticity

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8
Q

if observations are NOT independent, residuals from model will exhibit what?

A

serial correlation

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9
Q

what are the two necessary assumptions of linear regression analysis?

A

residuals are normally distributed and constant variance of error term

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