BUS ANALYTICS TEST 2
Rob is a financial manager with Sharez, an investment advisory company. He must select specific investments—for example, stocks and bonds—from a variety of investment alternatives. Restrictions on the type of permissible investments would be a __________ in this case.
constraint
A controllable input for a linear programming model is known as a
decision variable
The mean absolute error, mean squared error, and mean absolute percentage error are all methods to measure the accuracy of a forecast. These methods measure forecast accuracy by
determining how well a particular forecasting method is able to reproduce the time series data that are already available
In a linear programming model, the __________ assumption plus the nonnegativity constraints mean that decision variables can take on any value greater than or equal to zero.
divisibility
A time series with a seasonal pattern can be modeled by treating the season as a
dummy variables
In linear programming models of real problems, the occurrence of an unbounded solution means that the
problem formulation is improper
The __________ assumption necessary for a linear programming model to be appropriate means that the contribution to the objective function and the amount of resources used in each constraint are in accordance to the value of each decision variable
proportionality
Causal models
relate a time series to other variables that are believed to explain or cause its behavior
Constraints are
restrictions that limit the settings of the decision variables
For causal modeling, __________ are used to detect linear or nonlinear relationships between the independent and dependent variables.
scatter charts
A time series that shows a recurring pattern over one year or less is said to follow a
seasonal pattern
The study of how changes in the input parameters of a linear programming problem affect the optimal solution is known as
sensitivity analysis.
The change in the optimal objective function value per unit increase in the right-hand side of a constraint is given by the
shadow price
The reduced cost for a decision variable that appears in a Sensitivity Report refers to the __________ of the nonnegativity constraint for that variable.
shadow price
With reference to time series data patterns, a cyclical pattern is the component of the time series that
shows a periodic pattern lasting more than one year
Which algorithm, developed by George Dantzig and utilized by Excel Solver, is effective at investigating extreme points in an intelligent way to find the optimal solution to even very large linear programs?
simplex algorithm
The __________ value for each less-than-or-equal-to constraint indicates the difference between the left-hand and right-hand values for a constraint.
slack
With reference to exponential forecasting models, a parameter that provides the weight given to the most recent time series value in the calculation of the forecast value is known as the
smoothing constraint
Using a large value for order k in the moving averages method is effective in
smoothing out random fluctuations
A variable subtracted from the left-hand side of a greater-than-or-equal to constraint to convert the constraint into an equality is known as a(n)
surplus variable
Trend refers to
the long-run shift or movement in the time series observable over several periods of time.
An exponential trend pattern occurs when
the percentage change between periods in the value of the variable is relatively constant
Nonnegativity constraints ensure that
the solution to the problem will contain only nonnegative values for the decision variables
When formulating a constraint, care must be taken to ensure that
the units of measurement on both sides of the constraint match
If a time series plot exhibits a horizontal pattern, then
there is still not enough evidence to conclude that the time series is stationary
A set of observations on a variable measured at successive points in time or over successive periods of time constitute a
time series
Which of the following statements is the objective of the moving averages and exponential smoothing methods?
to smooth out random fluctuations in the time series
Problems with infeasible solutions arise in practice because
too many restrictions have been placed on the problem
The situation in which the value of the solution may be made infinitely large in a maximization linear programming problem or infinitely small in a minimization problem without violating any of the constraints is known as
unbounded
A positive forecast error indicates that the forecasting method ________ the dependent variable.
underestimated
The moving averages method refers to a forecasting method that
uses the average of the most recent data values in the time series as the forecast for the next period
The shadow price of nonbinding constraints
will always be zero
The slack value for binding constraints is
zero
Which of the following is true of the exponential smoothing coefficient?
It is chosen as the value that minimizes a selected measure of forecast accuracy such as the mean squared error
A canned food manufacturer has its manufacturing plants in three locations across a state. Their product has to be transported to 3 central distribution centers, which in turn disperse the goods to 72 stores across the state. Which of the following is most likely to be the objective function in this scenario?
Minimizing the cost of shipping goods from the plant to the store
Which of the following error messages is displayed in Excel Solver when attempting to solve an unbounded problem?
Objective Cell values do not converge
__________, or modeling, is the process of translating a verbal statement of a problem into a mathematical statement.
Problem formulation
Suppose that profit for a particular product is calculated using the linear equation: Profit = 20S + 3D. Which of the following combinations of S and D would yield a maximum profit?
S = 405, D = 0
stationary time series
The variability is constant over time. The statistical properties are independent of time. The process generating the data has a constant mean. NOT IN A STRAIGHT LINE
Which of the following states the objective of time series analysis?
To uncover a pattern in a time series and then extrapolate the pattern into the future
The moving averages and exponential smoothing methods are appropriate for a time series exhibiting
a horizontal pattern
The reduced cost for a decision variable that appears in a Sensitivity Report indicates the change in the optimal objective function value that results from changing the right-hand side of the nonnegativity constraint from
0 to 1
If the forecasted value of the time series variable for period 2 is 22.5 and the actual value observed for period 2 is 25, what is the forecast error in period 2?
2.5
The exponential smoothing forecast for period t + 1 is a weighted average of the
actual value in period t with weight α and the forecast for period t with weight 1 - α
The assumption that is necessary for a linear programming model to be appropriate and that ensures that the value of the objective function and the total resources used can be found by summing the objective function contribution and the resources used for all decision variables is known as
additivity
A scenario in which the optimal objective function contour line coincides with one of the binding constraint lines on the boundary of the feasible region leads to __________ solutions.
alternative optimal
A causal model provides evidence of __________ between an independent variable and the variable to be forecast.
an association
A(n) ___________ solution satisfies all the constraint expressions simultaneously.
feasible
__________ is the amount by which the predicted value differs from the observed value of the time series variable
forecast error
Geometrically, binding constraints intersect to form the
optimal point
trend patterns
Can result from factors such as improving technology or changes in consumer preferences Can represent nonlinear relationships Exist when there are gradual shifts of values over long periods of time Hide Feedback
A __________ refers to a constraint that can be expressed as an equality at the optimal solution.
binding constraint
__________ uses a weighted average of past time series values as the forecast.
exponential smoothing
The points where constraints intersect on the boundary of the feasible region are termed as the
extreme points
__________ is the situation in which no solution to the linear programming problem satisfies all the constraints.
infeasibility
Forecast error
is associated with measuring forecast accuracy
The value of an independent variable from the prior period is referred to as a
lagged variable
A mathematical function in which each variable appears in a separate term and is raised to the first power is known as a
linear function
Rob is a financial manager with Sharez, an investment advisory company. He must select specific investments—for example, stocks and bonds—from a variety of investment alternatives. Which of the following statements is most likely to be the objective function in this scenario?
maximization of expected return
Which of the following measures of forecast accuracy is susceptible to the problem of positive and negative forecast errors offsetting one another?
mean forecast error
A canned food manufacturer has its manufacturing plants in three locations across a state. Their product has to be transported to 3 central distribution centers, which in turn disperse the goods to 72 stores across the state. Which of the following visualization tools could help understand this problem better?
network graph
The process of __________ might be used to determine the value of the smoothing constant that minimizes the mean squared error.
nonlinear optimization
In the moving averages method, the order k determines the
number of time series values under consideration
The term __________ refers to the expression that defines the quantity to be maximized or minimized in a linear programming model.
objective function
A(n) __________ refers to a set of points that yield a fixed value of the objective function.
objective function contour
In problem formulation, the
objective is expressed in terms of the decision variables.
Autoregressive models
occur whenever all the independent variables are previous values of the time series