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SRM EXAM 2024 WITH ANSWERS AND ANSWERS
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SRM EXAM 2024 WITH ANSWERS ANDANSWERS
The variance of a statistical learning method decreases as the method's flexibility
increases - ANSWER False. Flexibility increases, Variance increases.
SST - ANSWER Total Sum of Squares. Sum of (yi - average y)^2
SSR - ANSWER Regression Sum of Squares. Sum of (y hat - yi)^2
SSE aka RSS - ANSWER Error Sum of Squares/Residual Sum of Squares. Sum of
(yi - y hat)^2
s^2 aka MSE - ANSWER SSE/(n-p-1)
Residual Standard Error - ANSWER Square rut of the MSE
R^2 - ANSWER coefficient of determination. SSR/SST. 1 - SSE/SST
t stat - ANSWER (b1 - B1)/ seb1
Which interval is always at least as wide as the other? - ANSWER A Prediction
interval is always at least as wide as the Confidence Interval.
If p-value is less than or equal to alpha - ANSWER Reject the Null Hypothesis
(the variable is significant)
R^2 adj - ANSWER 1- MSE/variance. 1 - (SSE/(n-p-1))/(SST=(n-1)). 1 -
(1-R^2)*((n-1)/(n-p-1))
The sum of residuals always = ________ - ANSWER p+1
A residual (hi) is always between ______ - ANSWER 1/n and 1. (1/n < hi < 1)
FREES: outlier if __________. - ANSWER standardized residual is > 2
FREES: high leverage point if hi > ___________ - ANSWER 3((p+1)/n)
FREES: Severe multicollinearity if ___________. - ANSWER VIF greater than or
equal to 10.
The logit and probit functions are substantially different. - ANSWER False.
, F-Stat (full) - ANSWER MSR/MSE. (SSR/p)/(SSE/(n-p-1))
F-stat (Partial) - ANSWER (SSEr - SSEf)/(pf-pr) / SSEf/(n-pf - 1)
What is the difference between a t test and an F test? - ANSWER T test: one
parameter at a time. F Test: more than one parameter at a time.
The sum of leverages in a model (hi) = ? - ANSWER p+1
How do you find the leverages in a matrix? - ANSWER They are the diagonal
elements of the Hat matrix
Cook's Distance formula? What is it for? - ANSWER Measuring leverage and
residuals in one formula. ((ei^2 * hi)/(1 - hi)^2) / MSE(p+1)
Heteroscedasticity - ANSWER Non-constant variance. Often takes on a funnel
shape when looking at a plot of residuals
What are AIC, BIC, and Mallow's Cp used for? - ANSWER They summarize the
tradeoff between model fit and complexity. Smallest value is desired.
T or F? We want predictable residuals. - ANSWER False. This means there are
dependent error terms.
How to fix heteroscedasticity? - ANSWER Transform response with a concave
function (log or square rut)
How to fix a u-shaped residuals plot? - ANSWER Add a polynomial term of
degree 2 to the model
One way you can detect multicollinearity by inspecting the residuals vs. fitted
values plot. - ANSWER False. You can inspect the correlation matrix or
calculate variance inflation factors.
VIFj = ? - ANSWER 1/(1-Rj^2)
T or F? Forward stepwise selection cannot be used in high-dimensional settings. -
ANSWER False. Forward stepwise selection can be used in high-dimensional
settings, backward stepwise cannot be used.
k-fold cross-validation is a special case of LOOCV. - ANSWER False. Opposite.
LOOCV has folds = # of observations.
Rank by Variance (least to greatest). validation set, k-fold, LOOCV - ANSWER
validation set < k-fold < LOOCV
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