QUANTECH Flashcards

(55 cards)

1
Q

7 Steps of Problem Solving

A
  • Define the problem.
  • Identify the set of alternative solutions.
  • Determine the criteria for evaluating alternatives.
  • Evaluate the alternatives.
  • Choose an alternative (make a decision).
  • Implement the chosen alternative.
  • Evaluate the results.
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2
Q

Reasons for using quantitative analysis:

A
  • The problem is complex.
  • The problem is very important.
  • The problem is new.
  • The problem is repetitive.
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3
Q

Quantitative Analysis Process

A
  1. Model Development
  2. Data Preparation
  3. Model Solution
  4. Report Generation
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4
Q

Types of Models

A
  1. Iconic
  2. Analog
  3. Mathematical
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5
Q

A type of model that involves physical replicas

A

Iconic

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6
Q

A type of model that involves Physical but not visually similar.

A

Analog

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7
Q

A type of model that Represent problems with formulas

A

Mathematical

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8
Q

Essential for accurate analysis, but time-consuming and prone to errors.

A

Data preparation

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9
Q

Involves user involvement, monitoring, and refining as necessary.

A

Model Implementation

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10
Q

The body of knowledge involving quantitative approaches to decision making is reffered to as:

A
  • Management Science
  • Operations Research
  • Decision Science
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11
Q

Must be made in selecting an appropriate mathematical model

A

Cost/benefit considerations

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12
Q

Mathematical models are said to be _____ if any of the uncontrollable inputs is subject to variation.

A

Stochastic

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13
Q

If any of the uncontrollable inputs in a mathematical model are NOT subject to variation, they are ___________

A

Deterministic

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14
Q

The values of the decision variables that provide the mathematically-best output are referred to as the _______ ________

A

Optimal Solution

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15
Q

Controllable Inputs are also called as

A

Decision Variables

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16
Q

Uncontrollable Inputs are also called as

A

Environmental Factors

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17
Q

Is an algebraic equation in which each term is either a
constant or the product of a constant and (the first power of) a single variable.

ax+by=c

A

Linear Equation

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18
Q

A visual representation of decisions (square nodes) and chance events (round nodes).

A

Decision Tree

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19
Q

Choose the decision with the largest payoff.

A

Optimistic Approach (Maximax)

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20
Q

Select the decision with the best worst-case scenario

A

Conservative Approach (Maximin)

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21
Q

Minimize potential regret

A

Minimax Regret Approach

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22
Q

Recognizes the variance between expected value and actual outcomes. helps the decision maker recognize the difference between:

the expected value of a decision alternative, and the payoff that might actually occur

A

Risk Analysis

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23
Q

Assesses how input changes affect recommended decisions. Can be used to determine how changes to the following inputs affect the recommended decision alternative: probabilities for the states of nature values of the payoffs

A

Sensitivity Analysis

24
Q

Initial estimates before sample information.

Prior to obtaining this information, the probability estimates for the states of nature are called

A

Prior Probabilities

25
Likelihoods based on states of nature It is a condition where the inequality is true for certain values of the unknown involved
Conditional Probabilities
26
Updates prior probabilities to posterior probabilities. These prior probabilities can be revised by employing what Theorem? can be used to compute branch probabilities for decision trees
Bayes' Theorem
27
Evaluates the usefulness of sample data is the ratio of EVSI to EVPI expressed as a percent
Efficiency of Sample Information (E)
28
is the first step of decision making. It is crucial as it sets the stage for the decision-making process, clarifying what needs to be addressed before exploring potential solutions or alternatives.
Definition of a Problem
29
are the ways to evaluate the choices faced by the decision maker. They serve as standards or benchmarks used to assess and compare different options when making a decision
Decision Criteria
30
A model that uses a system of symbols to represent a problem is called a
Mathematical Model
31
A physical model that does not have the same physical appearance as the object being modeled is an
Analog Model
32
Must occur prior to the quantitative analysis process, must involve the analyst and the user of the results, and includes specific objectives and operating constraints.
Problem Definition
33
The volume that results in total revenue being equal to total cost is the ________. At this point, there is neither profit nor loss.
Break-even point
34
When the value of the output cannot be determined even if the value of the controllable input is known, the model is?
Stochastic
35
A system of equations with no solution is called an
Inconsistent System
36
A system of equations with only one solution is called an
Consistent
37
A system of equations with multiple solutions is called an
Dependent
38
The quantitative analysis approach requires __________ __________ for the relationships.
Mathematical Expressions
39
is a statement that one quantity or expression is greater or less than another quantity or expression
Inequality
40
It is a condition where the inequality is true for all values of the unknown involved
Absolute Inequality
41
First step in decision analysis process
Problem Formulation
42
The consequence resulting from a specific combination of a decision alternative and a state of nature Can be expressed in terms of profit, cost, time, distance or any other appropriate measure.
Payoff
43
are representations of real objects or situations
Models
44
A table showing payoffs for all combinations of decision alternatives and states of nature
Payoff Table
45
is a graphical device showing the relationships among the decisions, the chance events, and the consequences
Influence Diagram
46
depict decision nodes
Squares or rectangles
47
depict chance nodes.
Circle
48
depict consequence nodes.
Diamonds
49
connecting the nodes show the direction of influence.
Lines or arcs
50
Leaving a round node represent the different states of nature; branches leaving a square node represent the different decision alternatives
Branches
51
correspond to chance events
Round nodes
52
to identify the best or recommended decision alternative. the sum of the weighted payoffs for the decision alternative.
Expected Value Approach
53
is the increase in the expected profit that would result if one knew with certainty which state of nature would occur. provides an upper bound on the expected value of any sample or survey information.
Expected value of perfect information (EVPI)
54
is the additional expected profit possible through knowledge of the sample or survey information
Expected Value of Sample Information
55
a decision alternative shows the possible payoffs for the decision alternative along with their associated probabilities
Risk profile