Ch. 1 Overview Flashcards

1
Q

A set of mathematical relationships and logical assumptions implemented in a computer as a representation of some real world situation, decision, problem, or phenomenon. Organizations use these to help make decisions.

Name an example of one of these.

A

Computer Model

Example: electronic spreadsheets is the best way to implement and analyze computer models

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2
Q

A computer model implemented via a spreadsheet

A

Spreadsheet Model

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3
Q

A field of study that uses data, computers, statistics, and mathematics to solve business problems. It involves using the methods and tools of science to drive decision making.

A

Business Analytics

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4
Q

Also referred to as operations research, management science or decision science.
Organizations can use analytics to identify the best decision alternatives for a given application or situation

A

Business Analytics

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5
Q

The current trend of business analytics is:

A

Increasing usage to gain competitive advantage
Focusing on business intergration
Growing Demand for analytics talent

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6
Q

To conduct business analytics you need:

A

Models
Human insights
Data

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7
Q

Picturing how something will look in your mind’s eye

A

Mental Model

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8
Q

set of drawings or blueprints for a house

A

Visual Model

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9
Q

uses a mathematical relationship to describe or represent an object or decision problem

A

Mathematical Model

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10
Q
  1. Delivers needed information on a more timely basis
  2. Helpful in examining situations that would be impossible to do in reality
  3. Less expensive than implementing several alternative solutions
A

Benefits of Mathematical Model

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11
Q

What is the dependent variable and independent variable in this equation: Profit = Revenue - Expenses

A

Profit depends on the revenue and expenses so it is the DEPENDENT VARIABLE

Revenue and Expenses are the INDEPENDENT VARIABLES

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12
Q

the number of independent variables involved is this. Also the relationship between the dependent and independent variables is this.

A

F = function

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13
Q

What does Y equal in the regression/time series equation

A

Y = the dependent variable

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14
Q

the value of the inputs in the cell

A

Input Cells

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15
Q

the results of the input cells

A

Output Cells

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16
Q

a model that accurately represents the relevant characteristics of the object or decision problem being studied

A

Valid Model

17
Q
  • the solutions tell the decision maker what actions to take
  • known well defined functions

-the independent variables are known or under the decision makers control

A

Prescriptive Models (OPTIMIZATION)

18
Q

Examples of Prescriptive Models

A

Examples: Linear Programming, Networks, Integer Programming, Goal Programming

Real world: Investment portfolio design and Airline Flight schedules

19
Q
  • the function might be unknown and must be estimated in order for the decision maker to make predictions about the dependent variables
  • unknown, ill defined functions

-the independent variables are known or under the decision makers control

A

Predictive Models (FORECASTING)

20
Q

Examples of Predictive Models

A

Examples: Regression Analysis, Time Series Analysis, Discriminant Analysis

Realworld: FICO credit scoring and Fraud Detection

21
Q
  • there is a well defined functional relationship, however there is great uncertainty as to the exact values that will be assumed by one or more of the independent variables
  • seeks to measure and explain situations
  • known, well-defined functions
  • the independent variables are unknown or uncertain
A

Descriptive Models (ANALYSIS)

22
Q

Examples of Descriptive Models

A

Examples: Simulation, Queuing, Inventory Models

Realworld: inventory turns and employee absenteeism

23
Q

Synonym for
Prescriptive Models

Predictive Models
Descriptive Models

A
  1. Prescriptive = Optimization
  2. Predictive = Forecasting
  3. Descriptive = Analysis
24
Q

5 steps to the Problem Solving Process (DECISION MAKING PROCESS)

A
  1. Identify Problem
  2. Formulate and Implement Model
  3. Analyze Model
  4. Test Results (if unsatisfactory result, go back to forumulate step)
  5. Implement Solutions (this is considered the most difficult step)
25
Q

Arise when a seemingly trivial factor serves as a starting point for estimations in a decision making problem

A

Anchoring Effects

26
Q

Refer to how a decision maker views or perceives the alternatives in a decision problem - involves a win/loss perspective

A

Framing Effects

27
Q

Good Bad
Good Deserved Success Bad Luck

Bad Dumb Luck Poetic Justice

A

Decision Quality

28
Q

the factor that plays a role in determining whether a good or bad outcome occurs regardless of the quality of the decision.

A

Chance

29
Q

Economy - its often less costly to analyze decision problems using models rather than trying out a decision

Timeliness - Models can often deliver needed
information more quickly than their real-world
counterparts.

Feasibility - Models can be used to do things
that would otherwise be impossible.

Understanding - Models often provide insights
that can improve the decision-making process.

A

Benefits of Modeling

30
Q

Machine learning example: Labeled data (X and Y) applications

Example: predicting sports outcomes based on team characteristics

A

Supervised Machine Learning

31
Q

unlabeled data is widespread and inexpensive to acquire, while labeled data is limited and expensive to acquire

Example: detecting employee fraud where most of the fraud cases remain unidentified

A

Semi-Supervised Machine Learning

32
Q

Unlabeled data only (X) applications

Example: reducing customer churn

A

Unsupervised Machine Learning

33
Q

What is a factor that illustrates a constraint.

A

Budget

34
Q

Break Even Model formula?

A

Break-Even point (units) = Fixed Costs ÷ (Sales price per unit – Variable costs per unit)

35
Q

describes many people using the cloud when working together on one project

A

E-collaboration

36
Q

type of management system includes the integration of technology and software across an organization

A

Enterprise resource planning systems