Multivariate Analysis Flashcards
1
Q
Ceteris paribus
A
holding all other variables constant, only way to isolate the effect of the variable of interest
2
Q
B0
A
predicted value of y when all x’s equal 0
3
Q
B1
A
predicted change in y when x increases by 1 unit, holding all other variables constant
4
Q
Multiple regression bias
A
- random sample
- linear in parameters
- no perfect correlation between variables
- cov(x,u) = 0
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
6
Q
sample size & 𝜎̂^2
A
Sample size will not effect sigma squared because n is in the numerator and denominator
7
Q
sample size and total sum of squares (SST)
A
will increase SST because it contains the sum of i to n
8
Q
k
A
- no. / new regressors
- increasing k, decreases the variance b/c it’s in the denominator