BARBER PRACTICE STATE BOARD
CERTIFICATION SCRIPT 2026
QUESTIONS WITH SOLUTIONS
GRADED A+
◍ What metric would you use to find best values of a, β, and γ to use for
training?.
Answer: SSEminimize over whole training set (model's best fit)
◍ What tool can help you determine if you need to use a Box-Cox
transformation?.
Answer: Q-Q plot
◍ Vertex.
Answer: Location in a network. In a network model, there is a constraint for
each vertex to ensure that the incoming flow equals the outgoing flow. Also
called a node.
◍ Paired samples.
Answer: Data with two different outcomes for each data point. Often helpful
for comparing the method that generated outcome #1 with the method that
generated outcome #2 to see which is better.
◍ Convex hull (of a set of points).
Answer: Smallest convex shape that the set of points is contained in.
◍ In the. equation for a classifier line, if aj is close to 0....
Answer: the attribute is not relevant
◍ Objective function.
Answer: Part of an optimization model that measures the quality of a
solution (the values of the variables).
,◍ What is C(t) in exponential smoothing?.
Answer: seasonality/cyclic factor
◍ Balanced design.
Answer: Set of combinations of factor values across multiple factors, that
has the same number of runs for all combinations of levels of one or more
factors.
◍ What are first order differences?.
Answer: observation at time t minus previous observation at time
t-1x(t)-x(t-1)
◍ What is ARIMA (p,0,0)?.
Answer: Autoregressive model
◍ K-means is considered a _____ maximization algorithm..
Answer: expectation
◍ Binary data.
Answer: Data that can take only two different values (true/false, 0/1,
black/white, on/off, etc.).
◍ What are standard data preparation steps?.
Answer: - scale the data (standardization/normalization)- outlier detection
◍ What is the goal of maximizing the space between support vectors?.
Answer: minimize classification error (more generalized model)
◍ Constraint.
Answer: Part of an optimization model that describes a restriction on the
solution (the values of the variables).
◍ Bernoulli distribution.
Answer: Discrete probability distribution where the outcome is binary,
either 0 or 1. Often, 1 represents success and 0 represents failure. The
probability of the outcome being 1 is and the probability of outcome
being 0 is = 1 − , where is between 0 and 1.
, ◍ What does p equal for manhattan distance?.
Answer: 1
◍ 0< BIC(1)-BIC(2) < 2.
Answer: smaller BIC model is "slightly likely" to be better
◍ Greedy algorithm.
Answer: Algorithm that makes the immediately-best choice at each step.
◍ Transition matrix.
Answer: Matrix of transition probabilities.
◍ ARIMA and exponential smoothing can be used for ___________
forecasting..
Answer: short-term
◍ Maximization problem.
Answer: Optimization model where the objective is to find the feasible
solution that maximizes the value of the objective function.
◍ Independent and identically distributed (iid).
Answer: Things that follow the same probability distribution, including the
same parameter(s), and whose values are independent of each other. For
example, multiple flips of the same coin are iid.
◍ Validation (of simulation).
Answer: Making sure that simulation results are similar-enough to those of
the real system being simulated, so the simulation can be used to analyze the
real system.
◍ Binary variable.
Answer: Variable that can take just two values: 0 and 1.
◍ When the classifier line is vertical....
Answer: (SVM) only x-axis matters in determining class
◍ Wilcoxon signed rank test (one sample).
Answer: Nonparametric test for a single response, to determining whether
the median is different from a specific value.
CERTIFICATION SCRIPT 2026
QUESTIONS WITH SOLUTIONS
GRADED A+
◍ What metric would you use to find best values of a, β, and γ to use for
training?.
Answer: SSEminimize over whole training set (model's best fit)
◍ What tool can help you determine if you need to use a Box-Cox
transformation?.
Answer: Q-Q plot
◍ Vertex.
Answer: Location in a network. In a network model, there is a constraint for
each vertex to ensure that the incoming flow equals the outgoing flow. Also
called a node.
◍ Paired samples.
Answer: Data with two different outcomes for each data point. Often helpful
for comparing the method that generated outcome #1 with the method that
generated outcome #2 to see which is better.
◍ Convex hull (of a set of points).
Answer: Smallest convex shape that the set of points is contained in.
◍ In the. equation for a classifier line, if aj is close to 0....
Answer: the attribute is not relevant
◍ Objective function.
Answer: Part of an optimization model that measures the quality of a
solution (the values of the variables).
,◍ What is C(t) in exponential smoothing?.
Answer: seasonality/cyclic factor
◍ Balanced design.
Answer: Set of combinations of factor values across multiple factors, that
has the same number of runs for all combinations of levels of one or more
factors.
◍ What are first order differences?.
Answer: observation at time t minus previous observation at time
t-1x(t)-x(t-1)
◍ What is ARIMA (p,0,0)?.
Answer: Autoregressive model
◍ K-means is considered a _____ maximization algorithm..
Answer: expectation
◍ Binary data.
Answer: Data that can take only two different values (true/false, 0/1,
black/white, on/off, etc.).
◍ What are standard data preparation steps?.
Answer: - scale the data (standardization/normalization)- outlier detection
◍ What is the goal of maximizing the space between support vectors?.
Answer: minimize classification error (more generalized model)
◍ Constraint.
Answer: Part of an optimization model that describes a restriction on the
solution (the values of the variables).
◍ Bernoulli distribution.
Answer: Discrete probability distribution where the outcome is binary,
either 0 or 1. Often, 1 represents success and 0 represents failure. The
probability of the outcome being 1 is and the probability of outcome
being 0 is = 1 − , where is between 0 and 1.
, ◍ What does p equal for manhattan distance?.
Answer: 1
◍ 0< BIC(1)-BIC(2) < 2.
Answer: smaller BIC model is "slightly likely" to be better
◍ Greedy algorithm.
Answer: Algorithm that makes the immediately-best choice at each step.
◍ Transition matrix.
Answer: Matrix of transition probabilities.
◍ ARIMA and exponential smoothing can be used for ___________
forecasting..
Answer: short-term
◍ Maximization problem.
Answer: Optimization model where the objective is to find the feasible
solution that maximizes the value of the objective function.
◍ Independent and identically distributed (iid).
Answer: Things that follow the same probability distribution, including the
same parameter(s), and whose values are independent of each other. For
example, multiple flips of the same coin are iid.
◍ Validation (of simulation).
Answer: Making sure that simulation results are similar-enough to those of
the real system being simulated, so the simulation can be used to analyze the
real system.
◍ Binary variable.
Answer: Variable that can take just two values: 0 and 1.
◍ When the classifier line is vertical....
Answer: (SVM) only x-axis matters in determining class
◍ Wilcoxon signed rank test (one sample).
Answer: Nonparametric test for a single response, to determining whether
the median is different from a specific value.
