Multivariate Analysis Flashcards

1
Q

Ceteris paribus

A

holding all other variables constant, only way to isolate the effect of the variable of interest

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2
Q

B0

A

predicted value of y when all x’s equal 0

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3
Q

B1

A

predicted change in y when x increases by 1 unit, holding all other variables constant

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4
Q

Multiple regression bias

A
  1. random sample
  2. linear in parameters
  3. no perfect correlation between variables
  4. cov(x,u) = 0
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5
Q

Perfect correlation

A

Can’t have 2 variables that add up to each other OR can’t have the same variable in 2 units of measurement

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6
Q

sample size & 𝜎̂^2

A

Sample size will not effect sigma squared because n is in the numerator and denominator

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7
Q

sample size and total sum of squares (SST)

A

will increase SST because it contains the sum of i to n

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8
Q

k

A
  • no. / new regressors

- increasing k, decreases the variance b/c it’s in the denominator

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