ISYE MIDTERM 2 | FALL | FINAL TEST 2026
QUESTIONS WITH CORRECT ANSWERS
GRADED A+
◍ Select the mathematical constraint that corresponds to the following: "Either
cheese sauce or peanut butter (or both) must be eaten with broccoli".In a diet
problem, let xi be the amount of food i in the solution (xi greater than or
equal to 0), and let M be the maximum amount that can be eating of any
food. Suppose we added new variables yi that are binary, if food i is eaten in
the solution, then it is part of the solution (yi = 1); otherwise yi = 0..
Answer: Ybroccoli is less than or equal to Ycheese_sauce + Ypeanut_butter
◍ Why are simple models better than complex ones.
Answer: less data is required; less chance of insignificant factors and easier
to interpret
◍ How do you choose t in LASSO.
Answer: use the lasso approach with different values of t and see which
gives the best trade off
◍ what is a Bernoulli distribution.
Answer: it's like a flipping coin. It can be used to model a single event and is
most useful when we put many of them together
◍ what is exploration?.
Answer: focusing on getting more information; in this case, to determine
with more certainty which ad is really the best
◍ what are the elements of simulation model?.
Answer: entities, modules, actions, resources, decisions point, and statistical
tracking
,◍ What is a balanced design?.
Answer: You test each choice the same # of times and each pair of choices
the same # of times
◍ what do we get without constraints in a network model if data is all integers.
Answer: an optimal solution where all the variables have integer values
◍ What is the structure of stochastic dynamic program.
Answer: dynamic program, but decisions have probabilities of next state
◍ What is elastic net?.
Answer: A variable selection method that works by minimizing the squared
error and constraining the combination of absolute values of coefficients and
their squares
◍ what is an example of a blocking factor.
Answer: The type of car, sports car or family car, is a blocking factor that it
could account for some of the difference between red cars and blue cars.
Because sports cars are more likely to be red; if we account for the
difference, we can reduce the variability in our estimates
◍ what type of test is McNemar's?.
Answer: binomial
◍ What are the advantages and disadvantages of imputing missing data with
the mean, median (numeric) or mode (categorical).
Answer: Advantage: hedge against being too wrong and easy to
computeDisadvantage: it can be biased imputation. Example people with
high income less likely to answer survey and thus the mean/median will
underestimate the missing value
◍ The figure above (question 14-17) shows the average of the first X
simulated wait times, as new replications ("runs") are run and added into the
overall average. It is not showing the wait time just for each replication. For
example, after X=101 replications, the wait time of the 101st replication is
not necessarily 72, but the average of those 101 replications is about 72.ii.
The simulation ___ even have been stopped after 5 runs (replications).
, (could/could not).
Answer: Could not
◍ What are the order of fastest to slowest optimization problems.
Answer: linear programs, convex quadratic programs, convex programs,
integer programs, general non-convex programs
◍ What are the pros and cons of Greedy Algorithms (Forward selection,
stepwise elimination, stepwise regression).
Answer: Good for initial analysis but often don't perform as well on other
data because they fit more to random effects than you'd like and appear to
have a better fit
◍ what does the Louvian algorithm do.
Answer: decompose a graph into communities
◍ what are constraints.
Answer: restrictions on variable names
◍ what are stochastic simulations?.
Answer: when there is randomness
◍ what is a key difference between stepwise regresson and lasso regression.
Answer: If the data is not scaled, the coefficients can have artificially
different orders of magnitude, which means they'll have unbalanced effects
on the lasso constraint.
◍ When should you not use imputation?.
Answer: When more than 5% of the data is moving per factor
◍ what is pure strategy.
Answer: just one choice (gas station)
◍ When is regression effective work well to determine important factors?.
Answer: If there aren't significant interactions between the factors.
◍ what are variables.
Answer: decisions to be made
QUESTIONS WITH CORRECT ANSWERS
GRADED A+
◍ Select the mathematical constraint that corresponds to the following: "Either
cheese sauce or peanut butter (or both) must be eaten with broccoli".In a diet
problem, let xi be the amount of food i in the solution (xi greater than or
equal to 0), and let M be the maximum amount that can be eating of any
food. Suppose we added new variables yi that are binary, if food i is eaten in
the solution, then it is part of the solution (yi = 1); otherwise yi = 0..
Answer: Ybroccoli is less than or equal to Ycheese_sauce + Ypeanut_butter
◍ Why are simple models better than complex ones.
Answer: less data is required; less chance of insignificant factors and easier
to interpret
◍ How do you choose t in LASSO.
Answer: use the lasso approach with different values of t and see which
gives the best trade off
◍ what is a Bernoulli distribution.
Answer: it's like a flipping coin. It can be used to model a single event and is
most useful when we put many of them together
◍ what is exploration?.
Answer: focusing on getting more information; in this case, to determine
with more certainty which ad is really the best
◍ what are the elements of simulation model?.
Answer: entities, modules, actions, resources, decisions point, and statistical
tracking
,◍ What is a balanced design?.
Answer: You test each choice the same # of times and each pair of choices
the same # of times
◍ what do we get without constraints in a network model if data is all integers.
Answer: an optimal solution where all the variables have integer values
◍ What is the structure of stochastic dynamic program.
Answer: dynamic program, but decisions have probabilities of next state
◍ What is elastic net?.
Answer: A variable selection method that works by minimizing the squared
error and constraining the combination of absolute values of coefficients and
their squares
◍ what is an example of a blocking factor.
Answer: The type of car, sports car or family car, is a blocking factor that it
could account for some of the difference between red cars and blue cars.
Because sports cars are more likely to be red; if we account for the
difference, we can reduce the variability in our estimates
◍ what type of test is McNemar's?.
Answer: binomial
◍ What are the advantages and disadvantages of imputing missing data with
the mean, median (numeric) or mode (categorical).
Answer: Advantage: hedge against being too wrong and easy to
computeDisadvantage: it can be biased imputation. Example people with
high income less likely to answer survey and thus the mean/median will
underestimate the missing value
◍ The figure above (question 14-17) shows the average of the first X
simulated wait times, as new replications ("runs") are run and added into the
overall average. It is not showing the wait time just for each replication. For
example, after X=101 replications, the wait time of the 101st replication is
not necessarily 72, but the average of those 101 replications is about 72.ii.
The simulation ___ even have been stopped after 5 runs (replications).
, (could/could not).
Answer: Could not
◍ What are the order of fastest to slowest optimization problems.
Answer: linear programs, convex quadratic programs, convex programs,
integer programs, general non-convex programs
◍ What are the pros and cons of Greedy Algorithms (Forward selection,
stepwise elimination, stepwise regression).
Answer: Good for initial analysis but often don't perform as well on other
data because they fit more to random effects than you'd like and appear to
have a better fit
◍ what does the Louvian algorithm do.
Answer: decompose a graph into communities
◍ what are constraints.
Answer: restrictions on variable names
◍ what are stochastic simulations?.
Answer: when there is randomness
◍ what is a key difference between stepwise regresson and lasso regression.
Answer: If the data is not scaled, the coefficients can have artificially
different orders of magnitude, which means they'll have unbalanced effects
on the lasso constraint.
◍ When should you not use imputation?.
Answer: When more than 5% of the data is moving per factor
◍ what is pure strategy.
Answer: just one choice (gas station)
◍ When is regression effective work well to determine important factors?.
Answer: If there aren't significant interactions between the factors.
◍ what are variables.
Answer: decisions to be made
