BUS 336 Midterm || with 100% Verified Solutions.
Quantitative analysis correct answers This is a scientific approach to managerial decision making
in which raw data are processed and manipulated to produce meaningful information.
Quantitative factors correct answers Factors that are data that can be accurately calculated. E.g.
different investment alternatives. interest rates, inventory levels, demand and labor cost.
Qualitative factors correct answers Factors that are more difficult to quantify but still affect the
decision process. E.g. the weather, state and federal legislation, technological breakthroughs.
Decision modeling correct answers A scientific approach that uses quantitative (mathematical)
techniques as a tool in managerial decision making. Also known as quantitative analysis,
management science, and operations research.
Model correct answers A representation (usually mathematical) of a practical problem scenario
or environment.
Types of decision models correct answers 1. Deterministic models
2. Probabilistic models
Deterministic models correct answers A model which assumes that all the relevant input data and
parameters are known with certainty. These models do not involve risk or chance. Examples of
deterministic models include the case of a computer production company, accounting
procedures, an appliance manufacturer, and a furniture manufacturer.
Probabilistic models correct answers A model which assumes that some input data are not known
with certainty. These models involve risk and chance. Examples of probabilistic models include
opening a new restaurant, investing in a stock, choosing a university major, and predicting the
weather.
Linear Programming (LP) correct answers This is the most commonly used deterministic
modelling technique.
Steps involved in decision modeling correct answers 1. Formulation
2. Solution
3. Interpretation
Iterative process correct answers A process based on repetition of steps and procedures. This is
done between each of the three steps in decision modeling to double check the validity of the
results.
Formulation correct answers The process by which each aspect of a problem scenario is
translated and expressed in terms of a mathematical model. This is the most important and
challenging step in the decision modelling process. The aim in formulation is to ensure that the
mathematical model completely addresses all three issues relevant to the problem at hand.
,Formulation can be further classified into three parts: (1) defining the problem, (2) developing a
model, (3) acquiring input data.
Defining the problem correct answers The first part in formulation (and in decision modeling) is
to develop a clear, concise statement of the problem. This statement gives direction and meaning
to all the parts that follow it. This may be the most important and difficult step. It is important to
go beyond the symptoms and identify the true causes. Specific and measurable objectives may
have to be developed.
Developing a model correct answers The second part in formulation. Once we select the problem
to be analyzed, the next part is to develop a decision model. The types of models include
physical, scale, schematic, and mathematical models. All models should be developed carefully.
They should be solvable, realistic, and easy to understand and modify, and the required input
data should be obtainable.
Mathematical model correct answers A model that is a set of mathematical relationships. In most
cases, these relationships are expressed as equations and inequalities, as they are in a spreadsheet
model that computes sums, averages, or standard deviations.
Variable correct answers A measurable quantity that may vary or that is subject to change. In
most cases, variables are unknown quantities.
Problem parameter correct answers A measurable quantity that is inherent in a problem. It
typically has a fixed and known value (i.e., a constant).
Acquiring input data correct answers The final step of formulation. Once we have developed a
model, we must obtain the input data to be used in the model. Input data may come from a
variety of sources - company reports, documents, employee interviews, direct measurement, or
statistical sampling.
Garbage in, garbage out (GIGO) correct answers This term means that improper data will result
in misleading results.
Solution step correct answers This is the second step of the decision modeling process. This step
is when the mathematical expressions resulting from the formulation process are actually solved
to identify the optimal solution. This solution step can be further classified into two parts: (1)
developing a solution and (2) testing the solution.
Developing a solution correct answers This is the first part of the solution step. Developing a
solution involves manipulating the model to arrive at the best (or optimal) solution to the
problem. Common techniques used for this include solving equations, trial and error, complete
enumeration and algorithms.
Complete enumeration correct answers Trying all possible values for the variables in the model
to arrive at the best decision.
, Algorithm correct answers A series of repeating steps to reach a solution.
Trial and error correct answers Trying various approaches and picking the best result.
Testing the solution correct answers Both input data and the model should be tested for accuracy
before analysis and implementation.
Interpretation and sensitivity analysis correct answers This is the third and final step of the
decision making process. This step revolves around how a manager can use the results/output
from the two previous steps (implementation/solution). It can be broken down into two parts: (1)
analyzing the results and sensitivity analysis and (2) implementing the results.
Analyzing the results and sensitivity analysis correct answers Analyzing the results starts with
determining the implications of the solution. In most cases, a solution to a problem will result in
some kind of action or change in the way an organization is operating. The implications of these
actions or changes must be determined and analyzed before the results are implemented. Because
a model is only an approximation of reality, the sensitivity of the solution to changes in the
model and input data is an important part of analyzing the results. This type of analysis is called
sensitivity, post-optimality, or what-if analysis. It is used to determine how much the solution
will change if there are changes in the model or the input data.
Sensitivity analysis correct answers A process that involves determining how sensitive a solution
is to changes in a different model or input data. When the optimal solution is very sensitive to
changes in the input data and the model specifications, additional testing must be performed to
make sure the model and input data are accurate and valid.
Implementing the results correct answers The final part of interpretation is to implement the
results. This can be much more difficult than one might imagine. After the solution has been
implemented, it should be closely monitored. Over time, there may be numerous changes that
call for modifications of the original solution. A changing economy, fluctuating demand, and
model enhancements requested by managers and decision makers are a few examples of changes
that might require an analysis to be modified.
Profit correct answers Profit = Revenue - Expenses
Profit = Revenue - (Fixed cost + Variable cost)
Profit = (Selling price per unit)(Number of units sold) - [Fixed cost + (Variable costs per unit)
(Number of units sold)]
Break-even point (BEP) correct answers The number of units sold that will result in total revenue
equaling total costs (i.e., profit is $0).
Break-even point (BEP) = Fixed cost ⁄ (Selling price per unit - Variable cost per unit)
Break-even point in dollars (BEP$) correct answers The sum of fixed and total variable cost if
the number of units sold equals the break-even point.
