Quant Flashcards
Formula for t-stat
t = [r √(n-2)] / [√(1-r^2)]
Confidence Intervals
Predicted Y +/- (critical t-value)*(standard error)
R^2 =
RSS/SST or (SST - SSE) / SST
RSS/SST =
(SST - SSE) / SST or R^2
SST =
RSS + SSE
MSR =
RSS / k ; (k = # of independent variables)
MSE =
SSE / (n-k-1) ; (k = # of independent variables)
SEE =
√(MSE) = Standard Error of Estimate
F =
MSR/ MSE or (RSS/k) / (SSE/(n-k-1))
Conditional Heteroskedasticity… its effect…
Residual variance related to level of independent variables… Too man Type 1 errors
Type 1 errors
The incorrect rejection of a true null hypothesis (a “false positive”)
Type 2 errors
The failure to reject a false null hypothesis (a “false negative”)
Serial Correlation… its effect…
Residuals are correlated… Type 1 errors (for positive correlation)
Multicollinearity.. its effect…
Two or more independent variable are correlated… Too many Type 2 errors
6 Misspsecifications of regression models
1) Omitting a variable
2) Transforming a variable
3) Incorrectly pooling data
4) Using a lagged dependent variable as an independent variable
5) Forecasting the past
6) Measuring independent variables w/ error