01. Which is an example of time series forecasting?
a) A dried fruit company sends out marketing postcards and models who will respond.
b) A glue manufacturer wants to know how long it will take for its glue to dry.
c) A fire department wants to know how many fires it will likely need to fight during the holidays, so that it can staff accordingly.
d) A hospital wants to know how long its patients will survive after open heart surgery so that adverse effects can be caught early.
02. The number of Lagrangian multipliers (dual values) in a given linear programming problem is equal to the number of what?
a) decision variables
b) objective functions
c) index sets
d) constraints
03. A company's goal is to generate best forecasts. Their focus is widget sales for the next thirty days from the current time interval. Typically, what is the preferred accumulation method and time interval for the data?
a) Weekly average
b) Weekly total
c) Monthly average
d) Monthly total
04. Which situation will result in an override conflict in SAS Visual Forecasting?
a) Two or more overrides cannot be reconciled for the same time period.
b) An override affects a combined model forecast.
c) An override is applied to an aggregated forecast, and one or more components of the aggregated forecast come from models having events or independent variables.
d) Two or more overrides exceed 100% APE.
05. Which elements are in the NEW set?
set FRUITS=/'Apple' 'Banana' 'Cherry'/;
set PIES=/'Apple' 'Pecan' 'Cherry'/;
set NEW = FRUITS symdiff PIES;
a) Apple, Cherry
b) Apple, Banana, Pecan, Cherry
c) Banana, Pecan
d) Apple, Apple, Banana, Pecan, Cherry, Cherry
06. Weighted performance measures like WAPE (weighted absolute percent error) are primarily useful for which task in a Model Studio forecasting project?
a) summarizing model performance for selecting a Champion pipeline for the project
b) correcting the bias found in unweighted performance measures in the process of selecting a champion pipeline for the project
c) selecting the champion model for an individual series in a pipeline for a project
d) choosing which series require overrides prior to choosing the champion pipeline for the project
07. Attribute variables are primarily useful to do what in a Model Studio Forecasting project?
a) Visualize the data and operate on generated forecasts outside the hierarchy defined by the project’s BY variables.
b) Define the project's data hierarchy, and visualize the level data contained in the attribute variable.
c) Visualize the project’s data hierarchy, and operate on generated forecasts inside the hierarchy.
d) Augment the project’s BY variables to define the data hierarchy for modeling and overrides.
08. Which sampling method is preferred for forecasting holdout assessment?
a) Draw simple random sample without replacement of about 25% of the series.
b) Draw simple random sample with replacement of about 50% of the series.
c) Sample first observations in the series, with at least four observations in the holdout data.
d) Sample last observations in the holdout data, with at least 4 observations in the fit data.
09. An ARIMA model forecast for two months past the end of the current month for a monthly time series is an example of which action?
a) Extrapolation
b) Accumulation
c) Aggregation
d) Seasonal adjustment
10. Which scenario can generate an Override conflict?
a) Underlying series with very different scales.
b) Two or more Overrides on a given series.
c) A log transformation of the statistical forecasts.
d) Two adjacent series that don’t nest within the data hierarchy.
Here are the sample questions which will help you be familiar with SAS Certified Specialist - Forecasting and Optimization Using SAS Viya (A00-407) exam style and structure. We encourage you to try our Demo SAS Viya Forecasting and Optimization Certification Practice Exam to measure your understanding of exam structure in an environment which simulates the SAS Viya Forecasting and Optimization Specialist Certification test environment.