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Worksheetsibis - chapter 11
Total questions: 163
Worksheet time: 1hrs 22mins
Name
Class
Date
1.
Managerial decision-making challenges
a)
finds the inputs necessary to achieve a goal such as a desired level of output.
b)
1. Managers need to analyze large amounts of information
c)
machine learning
d)
Strong AI
2.
2. Managers must make decisions quickly
a)
2. Managers must make decisions quickly
b)
Occur in situations in which a few established processes help to evaluate potential solutions, but not enough to lead to a definite recommended decision
c)
Top: Strategic
d)
Supervised
3.
3. Managers must apply sophisticated analysis techniques, such as Porter's strategies or forecasting, to make strategic decisions
a)
Occur in situations in which a few established processes help to evaluate potential solutions, but not enough to lead to a definite recommended decision
b)
3. Managers must apply sophisticated analysis techniques, such as Porter's strategies or forecasting, to make strategic decisions
c)
- reverse of consolidation
d)
analyze massive quantities of data to establish patterns and characteristics when the logic or rules are unknown
4.
The six-step decision-making process
a)
1. problem identification
b)
pie chart
c)
- a user can view regional sales data and then drill down all the way to each sales representative's data at each office.
d)
4. pivot
5.
2. data collection
a)
Encompasses all of the information contained within a single business process or unit of work, and its primary purpose is to support the performing of daily operational tasks
b)
2. data collection
c)
a mathematical method of handling imprecise or subjective information
d)
2. Sensitivity analysis
6.
3. solution generation
a)
a method whereby new problems are solved based on the solutions from similar cases solved in the past
b)
3. solution generation
c)
- Analyzing nonlinear relationships in information. (They have been called fancy regression analysis systems.)
d)
haptic interface
7.
4. solution test
a)
Affect how the firm is run from day to day.
b)
the process within a generic algorithm of randomly trying combinations and evaluating the success (or failure) of the outcome.
c)
4. solution test
8.
5. solution selection
a)
overfitting
b)
- enable employees to move beyond reporting to using the information to directly increase business performance
c)
5. solution selection
d)
- solve problems with incomplete information
9.
6. solution implementation
a)
- increase the speed and consistency of decision making
b)
6. solution implementation
c)
They are the domain of operations managers, who are the closest to the customer.
d)
The training of machine learning models to make a sequence of decisions
10.
Common Company Structure: Pyramid
a)
Supervised
b)
4. pivot
c)
arise in situations where established processes offer potential solutions
d)
Top: Strategic
11.
Middle: Managerial
a)
2. natural language understanding
b)
Middle: Managerial
c)
determines a user's intentions based on what the user typed or said
d)
enable high-level managers to examine and manipulate large amount of detailed data from different internal and external sources
12.
Bottom: Operational
a)
because they fill the gap when human experts are difficult to find or retain or are too expensive.
b)
Bottom: Operational
c)
determines a user's intentions based on what the user typed or said
d)
- Analyzing nonlinear relationships in information. (They have been called fancy regression analysis systems.)
13.
key business questions for the six-step decision-making process
a)
Top: Strategic
b)
1. problem identification
c)
Encompasses all of the information contained within a single business process or unit of work, and its primary purpose is to support the performing of daily operational tasks
d)
a process that employs specialized algorithms to model and study complex datasets; the method is also used to establish relationships among data and datasets
14.
2. data collection
a)
2. data collection
b)
a process that employs specialized algorithms to model and study complex datasets; the method is also used to establish relationships among data and datasets
c)
6. solution implementation
d)
stores large amounts of data with fast access
15.
3. solution generation
a)
3. solution generation
b)
managers develop overall business strategies, goals, and objectives as part of the company's strategic plan
c)
- can find and evaluate solutions with many more possibilities, faster, and more thoroughly than a human.
d)
occuring in situations in which no procedures or rules exist to guide decision makers toward the correct choice.
16.
4. solution test
a)
users would be able to observe and evaluate any changes that occured to the values in the model, especially to a variable such as profits
b)
checks the impact of a change in a variable or assumption on the model.
c)
Bottom: Operational
d)
4. solution test
17.
5. solution selection
a)
5. solution selection
b)
- lets managers view monthly, weekly, daily, or even hourly information
c)
short and medium range plans
d)
5. solution selection
18.
6. solution implementation
a)
Involve higher-level issues concerned with the overall direction of the organization. Define the organization's overall goals and aspirations for the future
b)
Employees develop, control, and maintain core business activities required to run the day-to-day operations
c)
the aggregation of data from simple roll-ups to complex groupings of interrelated information
d)
6. solution implementation
19.
Overview of Decision Making
a)
do not have a right or wrong answers, only efficient and effective answer
b)
- the only bias not associated with the input or training data.
c)
stores large amounts of data with fast access
20.
operational level
a)
- the only bias not associated with the input or training data.
b)
Employees develop, control, and maintain core business activities required to run the day-to-day operations
c)
checks the impact of a change in a variable or assumption on the model.
d)
- useful when users are uncertain about the assumptions made in estimating the value of certain key variables.
21.
operational decisions
a)
3. solution generation
b)
users would be able to observe and evaluate any changes that occured to the values in the model, especially to a variable such as profits
c)
Affect how the firm is run from day to day.
d)
occurs when there is a problem with the data collected that skews the data in one direction.
22.
They are the domain of operations managers, who are the closest to the customer.
a)
They are the domain of operations managers, who are the closest to the customer.
b)
4. knowledge planning
c)
A type of artificial intelligence that enables computers to both understand concepts in the environment, and also to learn.
d)
a mathematical property of an algorithm.
23.
structured decisions
a)
Employees develop, control, and maintain core business activities required to run the day-to-day operations
b)
arise in situations where established processes offer potential solutions
c)
a wearable computer with an optical head mounted display
d)
made frequently
24.
made frequently
a)
allocate resources
b)
a special case of what-if analysis, is the study of the impact on other variables when one variable is changed repeatedly.
c)
because they fill the gap when human experts are difficult to find or retain or are too expensive.
d)
made frequently
25.
almost repetitive in nature
a)
3. slice-and-dice
b)
almost repetitive in nature
c)
the aggregation of data from simple roll-ups to complex groupings of interrelated information
d)
- sets a target value (a goal) for a variable and then repeatedly changes other variables until the target value is achieved.
26.
affect short term business strategies
a)
structured decisions
b)
a process that employs specialized algorithms to model and study complex datasets; the method is also used to establish relationships among data and datasets
c)
Middle: Managerial
d)
an artificial intelligence system that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem
27.
examples of routine structured decisions
a)
the ability to look at information from different perspectives.
b)
stimulates human thinking and behavior, such as the ability to reason and learn
c)
reordering inventory
d)
Training a model to find patterns in a dataset, typically an unlabeled dataset.
28.
creating the employee staffing and weekly production schedules
a)
short and medium range plans
b)
2. Sensitivity analysis
c)
creating the employee staffing and weekly production schedules
d)
3. solution generation
29.
managerial level
a)
business objectives for the firm
b)
- sets a target value (a goal) for a variable and then repeatedly changes other variables until the target value is achieved.
c)
uses stored data to make predictions and decisions in real time such as goal-seeking analysis
d)
employees are continuously evaluating company operations to hone the firm's abilities to identify, adapt to, and leverage change
30.
managerial decisions cover:
a)
Unsupervised
b)
Top: Strategic
c)
3. Executive Information Systems
d)
short and medium range plans
31.
schedules and budgets along with policies
a)
a work environment that is not located in any one physical space
b)
- a user can view regional sales data and then drill down all the way to each sales representative's data at each office.
c)
schedules and budgets along with policies
d)
- can find and evaluate solutions with many more possibilities, faster, and more thoroughly than a human.
32.
procedures
a)
arise in situations where established processes offer potential solutions
b)
procedures
c)
Basic business system that serves the operational level and assists in making structured decisions
d)
- the reverse of what-if and sensitivity analysis.
33.
business objectives for the firm
a)
2. natural language understanding
b)
a mathematical method of handling imprecise or subjective information
c)
business objectives for the firm
d)
Encompasses all organizational information, and its primary purpose is to support the performing of managerial analysis tasks or semi-structured decisions
34.
allocate resources
a)
Unsupervised
b)
3. Executive Information Systems
c)
allocate resources
d)
1. natural language processing
35.
monitor the performance of organizational subunits
a)
4. Optimization analysis
b)
reordering inventory
c)
monitor the performance of organizational subunits
d)
made frequently
36.
Managerial Decisions
a)
concern how the organization should achieve the goals and objectives set by its strategy, and they are usually the responsibility of mid-level management
b)
Strong AI
c)
short and medium range plans
d)
users would be able to observe and evaluate any changes that occured to the values in the model, especially to a variable such as profits
37.
semistructured decisions
a)
produces graphical displays of patterns and complex relationships in large amounts of data
b)
Occur in situations in which a few established processes help to evaluate potential solutions, but not enough to lead to a definite recommended decision
c)
arise in situations where established processes offer potential solutions
d)
sparkline
38.
strategic level
a)
managers develop overall business strategies, goals, and objectives as part of the company's strategic plan
b)
A computer-simulated environment that can be a simulation of the real world or an imaginary world
c)
- resolve complicated issues that cannot be solved by conventional computing
d)
users would be able to observe and evaluate any changes that occured to the values in the model, especially to a variable such as profits
39.
strategic decisions
a)
- can rotate, stretch, and reflect each image to produce many variants of the original images to provide enough examples for training.
b)
- Learning and adjusting to new circumstances on their own.
c)
Involve higher-level issues concerned with the overall direction of the organization. Define the organization's overall goals and aspirations for the future
d)
Affect how the firm is run from day to day.
40.
unstructured decisions
a)
stores large amounts of data with fast access
b)
occuring in situations in which no procedures or rules exist to guide decision makers toward the correct choice.
c)
Top: Strategic
d)
a problem with using incorrect training data to train the machine
41.
model
a)
- can rotate, stretch, and reflect each image to produce many variants of the original images to provide enough examples for training.
b)
5. solution selection
c)
Describes the original transaction record along with details such as its date, purpose, and amount spent and includes cash receipts, canceled checks, invoices, customer refunds, employee time sheet, etc.
d)
a simplified representation or abstraction of reality
42.
Use of Models
a)
machine learning
b)
help managers calculate risks, understand uncertainty, change variables, and manipulate time to make decisions
c)
trends, sales, product statistics, and future growth projections
d)
6. solution implementation
43.
Primary Types of MIS Systems for Decision Making
a)
1. Transaction Processing System
b)
2. Decision Support Systems
c)
The training of machine learning models to make a sequence of decisions
d)
1. problem identification
44.
2. Decision Support Systems
a)
the aggregation of data from simple roll-ups to complex groupings of interrelated information
b)
2. Decision Support Systems
c)
- can rotate, stretch, and reflect each image to produce many variants of the original images to provide enough examples for training.
d)
a mathematical property of an algorithm.
45.
3. Executive Information Systems
a)
stimulates human thinking and behavior, such as the ability to reason and learn
b)
Bottom: Operational
c)
- Coping with huge volumes of information with many dependent variables.
d)
3. Executive Information Systems
46.
transactional information
a)
Encompasses all of the information contained within a single business process or unit of work, and its primary purpose is to support the performing of daily operational tasks
b)
- reverse of consolidation
c)
procedures
d)
Strong AI
47.
Online Transaction Processing (OLTP)
a)
the capture of transaction and event information using technology to (1) process the information according to defined business rules, (2) store the information, and (3) update existing information to reflect the new information
b)
- reverse of consolidation
c)
neural networks
d)
the ability to look at information from different perspectives.
48.
Transaction Processing System (TPS)
a)
1. Transaction Processing System
b)
Training a model from input data and its corresponding labels. Supervised machine learning is analogous to a student learning a subject by studying a set of questions and their corresponding answers. After mastering the mapping between questions and answers, the student can then provide answers to new (never-before-seen) questions on the same topic. Compare with unsupervised machine learning.
c)
Basic business system that serves the operational level and assists in making structured decisions
d)
2. Decision Support Systems
49.
source documents
a)
made frequently
b)
bar chart
c)
Describes the original transaction record along with details such as its date, purpose, and amount spent and includes cash receipts, canceled checks, invoices, customer refunds, employee time sheet, etc.
d)
2. drill-down
50.
system thinking example of a TPS
a)
sparkline
b)
4. solution test
c)
procedures
51.
analytical information
a)
time-series chart
b)
determines a user's intentions based on what the user typed or said
c)
2. Sensitivity analysis
d)
Encompasses all organizational information, and its primary purpose is to support the performing of managerial analysis tasks or semi-structured decisions
52.
examples of analytical information
a)
- Coping with huge volumes of information with many dependent variables.
b)
trends, sales, product statistics, and future growth projections
c)
an extension of goal-seeking analysis, finds the optimum value for a target variable by repeatedly changing other variables, subject to specified constraints
d)
computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems.
53.
Online Analytical Processing (OLAP)
a)
Manipulation of information to create business intelligence in support of strategic decision making
b)
because they fill the gap when human experts are difficult to find or retain or are too expensive.
c)
short and medium range plans
d)
6. solution implementation
54.
Decision Support System (DSS)
a)
Encompasses all of the information contained within a single business process or unit of work, and its primary purpose is to support the performing of daily operational tasks
b)
3. Managers must apply sophisticated analysis techniques, such as Porter's strategies or forecasting, to make strategic decisions
c)
Bottom: Operational
d)
provides assistance in evaluating and choosing among different courses of action
55.
pros of DSS
a)
enable high-level managers to examine and manipulate large amount of detailed data from different internal and external sources
b)
- can be avoided by collecting additional data using different devices.
c)
1. consolidation
d)
a category of AI that attempts to emulate the way the human brain works
56.
Common DSS Analysis Techniques
a)
1. What-if analysis
b)
to quickly communicate a message, to simplify the presentation of large amounts of data, to see data patterns and relationships, and monitor changes in variables over time.
c)
the process within a generic algorithm of randomly trying combinations and evaluating the success (or failure) of the outcome.
d)
4. solution test
57.
2. Sensitivity analysis
a)
a method whereby new problems are solved based on the solutions from similar cases solved in the past
b)
2. Sensitivity analysis
c)
Weak AI
d)
- resolve complicated issues that cannot be solved by conventional computing
58.
3. Goal-seeking analysis
a)
time-series chart
b)
histogram
c)
3. Goal-seeking analysis
d)
Measurement bias
59.
4. Optimization analysis
a)
enable high-level managers to examine and manipulate large amount of detailed data from different internal and external sources
b)
- the reverse of what-if and sensitivity analysis.
c)
4. Optimization analysis
d)
Unsupervised
60.
what-if analysis
a)
- sets a target value (a goal) for a variable and then repeatedly changes other variables until the target value is achieved.
b)
time-series chart
c)
refers to the field of AI that works toward providing brainlike powers to AI machines, in effect, it works to make machines as intelligent as humans
d)
checks the impact of a change in a variable or assumption on the model.
61.
users would be able to observe and evaluate any changes that occured to the values in the model, especially to a variable such as profits
a)
- resolve complicated issues that cannot be solved by conventional computing
b)
analyze massive quantities of data to establish patterns and characteristics when the logic or rules are unknown
c)
users would be able to observe and evaluate any changes that occured to the values in the model, especially to a variable such as profits
d)
a work environment that is not located in any one physical space
62.
sensitivity analysis
a)
a special case of what-if analysis, is the study of the impact on other variables when one variable is changed repeatedly.
b)
Sample bias
c)
time-series chart
d)
3. Goal-seeking analysis
63.
- useful when users are uncertain about the assumptions made in estimating the value of certain key variables.
a)
4. solution test
b)
computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems.
c)
- useful when users are uncertain about the assumptions made in estimating the value of certain key variables.
d)
structured decisions
64.
goal-seeking analysis
a)
finds the inputs necessary to achieve a goal such as a desired level of output.
b)
- can be avoided by collecting additional data using different devices.
c)
analyze massive quantities of data to establish patterns and characteristics when the logic or rules are unknown
d)
- reverse of consolidation
65.
- the reverse of what-if and sensitivity analysis.
a)
the viewing of the physical world with computer-generated layers of information added to it
b)
3. solution generation
c)
a method whereby new problems are solved based on the solutions from similar cases solved in the past
d)
- the reverse of what-if and sensitivity analysis.
66.
- sets a target value (a goal) for a variable and then repeatedly changes other variables until the target value is achieved.
a)
occurs when adding additional training examples by transforming existing examples
b)
underfitting
c)
- sets a target value (a goal) for a variable and then repeatedly changes other variables until the target value is achieved.
d)
the capture of transaction and event information using technology to (1) process the information according to defined business rules, (2) store the information, and (3) update existing information to reflect the new information
67.
optimization analysis
a)
- Learning and adjusting to new circumstances on their own.
b)
an extension of goal-seeking analysis, finds the optimum value for a target variable by repeatedly changing other variables, subject to specified constraints
c)
3. Executive Information Systems
d)
1. What-if analysis
68.
Executive information system (EIS)
a)
a category of AI that attempts to emulate the way the human brain works
b)
3. Managers must apply sophisticated analysis techniques, such as Porter's strategies or forecasting, to make strategic decisions
c)
Transfer
d)
a specialized DSS that supports senior-level executives and unstructured, long-term, nonroutine decisions requiring judgement, evaluation and insight.
69.
EIS decisions
a)
Manipulation of information to create business intelligence in support of strategic decision making
b)
6. solution implementation
c)
Weak AI
d)
do not have a right or wrong answers, only efficient and effective answer
70.
granularity
a)
a mathematical property of an algorithm.
b)
a special case of what-if analysis, is the study of the impact on other variables when one variable is changed repeatedly.
c)
finds the inputs necessary to achieve a goal such as a desired level of output.
d)
refers to the level of detail in the model or the decision-making process
71.
visualization
a)
produces graphical displays of patterns and complex relationships in large amounts of data
b)
- the reverse of what-if and sensitivity analysis.
c)
a simplified representation or abstraction of reality
d)
1. Transaction Processing System
72.
infographic
a)
Employees develop, control, and maintain core business activities required to run the day-to-day operations
b)
a representation of information in a graphic format designed to make the data easily understandable at a glance
c)
occurs when adding additional training examples by transforming existing examples
d)
determines a user's intentions based on what the user typed or said
73.
use of infographic
a)
a representation of information in a graphic format designed to make the data easily understandable at a glance
b)
to quickly communicate a message, to simplify the presentation of large amounts of data, to see data patterns and relationships, and monitor changes in variables over time.
c)
Occur in situations in which a few established processes help to evaluate potential solutions, but not enough to lead to a definite recommended decision
d)
- useful when users are uncertain about the assumptions made in estimating the value of certain key variables.
74.
common elements of infographic
a)
histogram
b)
provides assistance in evaluating and choosing among different courses of action
c)
pie chart
d)
a wearable computer with an optical head mounted display
75.
bar chart
a)
2. natural language understanding
b)
bar chart
c)
Basic business system that serves the operational level and assists in making structured decisions
d)
4. solution test
76.
histogram
a)
A computer-simulated environment that can be a simulation of the real world or an imaginary world
b)
can still make their own decisions based on reasoning and past sets of data
c)
histogram
d)
stores large amounts of data with fast access
77.
sparkline
a)
- resolve complicated issues that cannot be solved by conventional computing
b)
a mathematical method of handling imprecise or subjective information
c)
3. Executive Information Systems
d)
sparkline
78.
time-series chart
a)
time-series chart
b)
5. solution selection
c)
Unsupervised
79.
digital dashboard
a)
computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems.
b)
6. solution implementation
c)
uses stored data to make predictions and decisions in real time such as goal-seeking analysis
d)
tracks KPIs and CSFs by compiling information from multiple sources and tailoring it to meet user needs
80.
pros of digital dashboard
a)
a wearable computer with an optical head mounted display
b)
- enable employees to move beyond reporting to using the information to directly increase business performance
c)
structured decisions
d)
2. Decision Support Systems
81.
- employees can react to information as soon as it becomes available and make decisions, solve problems, and change strategies daily instead of monthly
a)
- employees can react to information as soon as it becomes available and make decisions, solve problems, and change strategies daily instead of monthly
b)
- enable employees to move beyond reporting to using the information to directly increase business performance
c)
made frequently
d)
Strong AI
82.
Digital Dashboard Analytical Capabilities
a)
creating the employee staffing and weekly production schedules
b)
1. consolidation
c)
the aggregation of data from simple roll-ups to complex groupings of interrelated information
d)
A type of artificial intelligence that enables computers to both understand concepts in the environment, and also to learn.
83.
2. drill-down
a)
1. Managers need to analyze large amounts of information
b)
a wearable computer with an optical head mounted display
c)
2. drill-down
d)
the viewing of the physical world with computer-generated layers of information added to it
84.
3. slice-and-dice
a)
3. slice-and-dice
b)
4. pivot
c)
virtual reality
d)
the viewing of the physical world with computer-generated layers of information added to it
85.
4. pivot
a)
4. pivot
b)
Sample bias
c)
- enable employees to move beyond reporting to using the information to directly increase business performance
86.
consolidation
a)
the aggregation of data from simple roll-ups to complex groupings of interrelated information
b)
2. Decision Support Systems
c)
- Analyzing nonlinear relationships in information. (They have been called fancy regression analysis systems.)
d)
- can find and evaluate solutions with many more possibilities, faster, and more thoroughly than a human.
87.
drill-down
a)
- lets managers view monthly, weekly, daily, or even hourly information
b)
enables users to view details, and details of details, of information.
c)
3. Goal-seeking analysis
d)
6. solution implementation
88.
- reverse of consolidation
a)
- reverse of consolidation
b)
to ensure the training data has enough data to train the model
c)
3. Goal-seeking analysis
d)
A computer-simulated environment that can be a simulation of the real world or an imaginary world
89.
- a user can view regional sales data and then drill down all the way to each sales representative's data at each office.
a)
can still make their own decisions based on reasoning and past sets of data
b)
- increase the speed and consistency of decision making
c)
- a user can view regional sales data and then drill down all the way to each sales representative's data at each office.
d)
structured decisions
90.
- lets managers view monthly, weekly, daily, or even hourly information
a)
- lets managers view monthly, weekly, daily, or even hourly information
b)
Unsupervised
c)
determines a user's intentions based on what the user typed or said
91.
slice-and-dice
a)
the ability to look at information from different perspectives.
b)
a result of training data that is influenced by cultural or other stereotypes.
c)
occuring in situations in which no procedures or rules exist to guide decision makers toward the correct choice.
d)
- Functioning without complete or well-structured information.
92.
- often performed along a time axis to analyze trends and find time-based patterns in the information
a)
- often performed along a time axis to analyze trends and find time-based patterns in the information
b)
a category of AI that attempts to emulate the way the human brain works
c)
Describes the original transaction record along with details such as its date, purpose, and amount spent and includes cash receipts, canceled checks, invoices, customer refunds, employee time sheet, etc.
d)
Weak AI
93.
Pivot (rotation)
a)
A computer-simulated environment that can be a simulation of the real world or an imaginary world
b)
rotates data to display alternative presentations of the data
c)
- Coping with huge volumes of information with many dependent variables.
d)
1. Managers need to analyze large amounts of information
94.
artificial intelligence (AI)
a)
stimulates human thinking and behavior, such as the ability to reason and learn
b)
3. Goal-seeking analysis
c)
short and medium range plans
d)
uses stored data to make predictions and decisions in real time such as goal-seeking analysis
95.
AI's ultimate goal
a)
Training a model from input data and its corresponding labels. Supervised machine learning is analogous to a student learning a subject by studying a set of questions and their corresponding answers. After mastering the mapping between questions and answers, the student can then provide answers to new (never-before-seen) questions on the same topic. Compare with unsupervised machine learning.
b)
4. knowledge planning
c)
- Coping with huge volumes of information with many dependent variables.
d)
to build a system that can mimic human intelligence
96.
pros of AI
a)
a simplified representation or abstraction of reality
b)
6. solution implementation
c)
4. Optimization analysis
d)
- increase the speed and consistency of decision making
97.
- solve problems with incomplete information
a)
A type of artificial intelligence that enables computers to both understand concepts in the environment, and also to learn.
b)
- solve problems with incomplete information
c)
a simplified representation or abstraction of reality
d)
- Lending themselves to massive parallel processing.
98.
- resolve complicated issues that cannot be solved by conventional computing
a)
- resolve complicated issues that cannot be solved by conventional computing
b)
Describes the original transaction record along with details such as its date, purpose, and amount spent and includes cash receipts, canceled checks, invoices, customer refunds, employee time sheet, etc.
c)
to build a system that can mimic human intelligence
d)
1. natural language processing
99.
categories of AI
a)
3. Executive Information Systems
b)
3. Goal-seeking analysis
c)
Weak AI
d)
users would be able to observe and evaluate any changes that occured to the values in the model, especially to a variable such as profits
100.
Strong AI
a)
Involve higher-level issues concerned with the overall direction of the organization. Define the organization's overall goals and aspirations for the future
b)
Strong AI
c)
4. Optimization analysis
101.
Weak AI
a)
provides assistance in evaluating and choosing among different courses of action
b)
can still make their own decisions based on reasoning and past sets of data
c)
to build a system that can mimic human intelligence
d)
a process that employs specialized algorithms to model and study complex datasets; the method is also used to establish relationships among data and datasets
102.
Strong AI
a)
refers to the field of AI that works toward providing brainlike powers to AI machines, in effect, it works to make machines as intelligent as humans
b)
a result of training data that is influenced by cultural or other stereotypes.
c)
- the primary issue with prejudice bias is that the training data decisions consciously or unconsciously reflect cultural and social stereotypes.
d)
a process that employs specialized algorithms to model and study complex datasets; the method is also used to establish relationships among data and datasets
103.
four areas of AI primary overview
a)
refers to the field of AI that works toward providing brainlike powers to AI machines, in effect, it works to make machines as intelligent as humans
b)
stores large amounts of data with fast access
c)
machine learning
d)
1. natural language processing
104.
2. natural language understanding
a)
2. natural language understanding
b)
2. data collection
c)
monitor the performance of organizational subunits
d)
Affect how the firm is run from day to day.
105.
3. knowledge representation
a)
Affect how the firm is run from day to day.
b)
a representation of information in a graphic format designed to make the data easily understandable at a glance
c)
- reverse of consolidation
d)
3. knowledge representation
106.
4. knowledge planning
a)
Employees develop, control, and maintain core business activities required to run the day-to-day operations
b)
tracks KPIs and CSFs by compiling information from multiple sources and tailoring it to meet user needs
c)
4. knowledge planning
d)
neural networks
107.
natural language processing
a)
overfitting
b)
Training a model from input data and its corresponding labels. Supervised machine learning is analogous to a student learning a subject by studying a set of questions and their corresponding answers. After mastering the mapping between questions and answers, the student can then provide answers to new (never-before-seen) questions on the same topic. Compare with unsupervised machine learning.
c)
uses language as an input that a computer system can decipher and act upon its meaning, such as Siri and Alexa
d)
to build a system that can mimic human intelligence
108.
natural language understanding
a)
because they fill the gap when human experts are difficult to find or retain or are too expensive.
b)
2. Sensitivity analysis
c)
A computer-simulated environment that can be a simulation of the real world or an imaginary world
d)
determines a user's intentions based on what the user typed or said
109.
knowledge representation
a)
provides assistance in evaluating and choosing among different courses of action
b)
a process that employs specialized algorithms to model and study complex datasets; the method is also used to establish relationships among data and datasets
c)
- happens when a model learns the details in the training data to the extent that it negatively impacts the performance of the model on new data
d)
stores large amounts of data with fast access
110.
knowledge planning
a)
2. natural language understanding
b)
occurs when adding additional training examples by transforming existing examples
c)
neural networks
d)
uses stored data to make predictions and decisions in real time such as goal-seeking analysis
111.
expert systems
a)
a mathematical property of an algorithm.
b)
computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems.
c)
uses stored data to make predictions and decisions in real time such as goal-seeking analysis
d)
Employees develop, control, and maintain core business activities required to run the day-to-day operations
112.
why is expert system are the most common form of AI in the business arena?
a)
2. drill-down
b)
uses language as an input that a computer system can decipher and act upon its meaning, such as Siri and Alexa
c)
because they fill the gap when human experts are difficult to find or retain or are too expensive.
d)
Middle: Managerial
113.
case-based reasoning
a)
a method whereby new problems are solved based on the solutions from similar cases solved in the past
b)
procedures
c)
- useful when users are uncertain about the assumptions made in estimating the value of certain key variables.
d)
to ensure the training data has enough data to train the model
114.
algorithms
a)
mathematical formulas placed in software that performs an analysis on a data set
b)
3. knowledge representation
c)
Middle: Managerial
d)
- Lending themselves to massive parallel processing.
115.
genetic algorithm
a)
an artificial intelligence system that mimics the evolutionary, survival-of-the-fittest process to generate increasingly better solutions to a problem
b)
an extension of goal-seeking analysis, finds the optimum value for a target variable by repeatedly changing other variables, subject to specified constraints
c)
sparkline
d)
allocate resources
116.
- an optimizing system; it finds the combination of inputs that gives the best outputs.
a)
arise in situations where established processes offer potential solutions
b)
3. Managers must apply sophisticated analysis techniques, such as Porter's strategies or forecasting, to make strategic decisions
c)
tracks KPIs and CSFs by compiling information from multiple sources and tailoring it to meet user needs
d)
- an optimizing system; it finds the combination of inputs that gives the best outputs.
117.
- best suited to decision-making environments in which thousands or millions of solutions are possible.
a)
machine learning
b)
- best suited to decision-making environments in which thousands or millions of solutions are possible.
c)
occurs when a machine learning model matches the training data so closely that the model fails to make correct predictions on new data
d)
schedules and budgets along with policies
118.
- can find and evaluate solutions with many more possibilities, faster, and more thoroughly than a human.
a)
the process within a generic algorithm of randomly trying combinations and evaluating the success (or failure) of the outcome.
b)
analyze massive quantities of data to establish patterns and characteristics when the logic or rules are unknown
c)
1. natural language processing
d)
- can find and evaluate solutions with many more possibilities, faster, and more thoroughly than a human.
119.
mutation
a)
to ensure the training data has enough data to train the model
b)
the ability to look at information from different perspectives.
c)
- best suited to decision-making environments in which thousands or millions of solutions are possible.
d)
the process within a generic algorithm of randomly trying combinations and evaluating the success (or failure) of the outcome.
120.
three primary areas of AI
a)
2. data collection
b)
machine learning
c)
short and medium range plans
d)
a mathematical method of handling imprecise or subjective information
121.
neural networks
a)
stores large amounts of data with fast access
b)
neural networks
c)
occuring in situations in which no procedures or rules exist to guide decision makers toward the correct choice.
d)
occurs when a learning machine model has poor predictive abilities because it did not learn the complexity in the training data
122.
virtual reality
a)
6. solution implementation
b)
virtual reality
c)
rotates data to display alternative presentations of the data
d)
1. Managers need to analyze large amounts of information
123.
machine learning
a)
neural networks
b)
occurs when adding additional training examples by transforming existing examples
c)
users would be able to observe and evaluate any changes that occured to the values in the model, especially to a variable such as profits
d)
A type of artificial intelligence that enables computers to both understand concepts in the environment, and also to learn.
124.
Types of Machine Learning
a)
Supervised
b)
a representation of information in a graphic format designed to make the data easily understandable at a glance
c)
short and medium range plans
d)
They are the domain of operations managers, who are the closest to the customer.
125.
Unsupervised
a)
creating the employee staffing and weekly production schedules
b)
analyze massive quantities of data to establish patterns and characteristics when the logic or rules are unknown
c)
- useful when users are uncertain about the assumptions made in estimating the value of certain key variables.
d)
Unsupervised
126.
Transfer
a)
Transfer
b)
- the only bias not associated with the input or training data.
c)
determines a user's intentions based on what the user typed or said
d)
to quickly communicate a message, to simplify the presentation of large amounts of data, to see data patterns and relationships, and monitor changes in variables over time.
127.
Supervised Machine Learning
a)
1. consolidation
b)
Training a model from input data and its corresponding labels. Supervised machine learning is analogous to a student learning a subject by studying a set of questions and their corresponding answers. After mastering the mapping between questions and answers, the student can then provide answers to new (never-before-seen) questions on the same topic. Compare with unsupervised machine learning.
c)
- the reverse of what-if and sensitivity analysis.
d)
structured decisions
128.
Unsupervised Machine Learning
a)
2. Managers must make decisions quickly
b)
- resolve complicated issues that cannot be solved by conventional computing
c)
Training a model to find patterns in a dataset, typically an unlabeled dataset.
d)
occurs when a machine learning model matches the training data so closely that the model fails to make correct predictions on new data
129.
transfer machine learning
a)
transferring information from one machine learning task to another
b)
1. Transaction Processing System
c)
They are the domain of operations managers, who are the closest to the customer.
d)
a special case of what-if analysis, is the study of the impact on other variables when one variable is changed repeatedly.
130.
the secret to build a successful machine learning models
a)
3. Executive Information Systems
b)
pie chart
c)
to ensure the training data has enough data to train the model
d)
- useful when users are uncertain about the assumptions made in estimating the value of certain key variables.
131.
Data Augmentation
a)
- happens when a model learns the details in the training data to the extent that it negatively impacts the performance of the model on new data
b)
a mathematical method of handling imprecise or subjective information
c)
occurs when adding additional training examples by transforming existing examples
d)
the ability to look at information from different perspectives.
132.
- can rotate, stretch, and reflect each image to produce many variants of the original images to provide enough examples for training.
a)
uses stored data to make predictions and decisions in real time such as goal-seeking analysis
b)
A type of artificial intelligence that enables computers to both understand concepts in the environment, and also to learn.
c)
- can rotate, stretch, and reflect each image to produce many variants of the original images to provide enough examples for training.
d)
schedules and budgets along with policies
133.
additional learning problems
a)
a category of AI that attempts to emulate the way the human brain works
b)
neural networks
c)
2. drill-down
d)
overfitting
134.
underfitting
a)
sparkline
b)
a wearable computer with an optical head mounted display
c)
Weak AI
d)
underfitting
135.
overfitting
a)
a process that employs specialized algorithms to model and study complex datasets; the method is also used to establish relationships among data and datasets
b)
Employees develop, control, and maintain core business activities required to run the day-to-day operations
c)
The training of machine learning models to make a sequence of decisions
d)
occurs when a machine learning model matches the training data so closely that the model fails to make correct predictions on new data
136.
- happens when a model learns the details in the training data to the extent that it negatively impacts the performance of the model on new data
a)
- solve problems with incomplete information
b)
can still make their own decisions based on reasoning and past sets of data
c)
They are the domain of operations managers, who are the closest to the customer.
d)
- happens when a model learns the details in the training data to the extent that it negatively impacts the performance of the model on new data
137.
underfitting
a)
Top: Strategic
b)
occurs when a learning machine model has poor predictive abilities because it did not learn the complexity in the training data
c)
a simplified representation or abstraction of reality
d)
computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems.
138.
Four types of bias in machine learning
a)
Sample bias
b)
enable high-level managers to examine and manipulate large amount of detailed data from different internal and external sources
c)
4. solution test
d)
occurs when there is a problem with the data collected that skews the data in one direction.
139.
Prejudice bias
a)
- Analyzing nonlinear relationships in information. (They have been called fancy regression analysis systems.)
b)
because they fill the gap when human experts are difficult to find or retain or are too expensive.
c)
uses stored data to make predictions and decisions in real time such as goal-seeking analysis
d)
Prejudice bias
140.
Measurement bias
a)
pie chart
b)
Measurement bias
c)
- resolve complicated issues that cannot be solved by conventional computing
d)
a category of AI that attempts to emulate the way the human brain works
141.
Variance bias
a)
produces graphical displays of patterns and complex relationships in large amounts of data
b)
Employees develop, control, and maintain core business activities required to run the day-to-day operations
c)
They are the domain of operations managers, who are the closest to the customer.
d)
Variance bias
142.
sample bias
a)
a problem with using incorrect training data to train the machine
b)
do not have a right or wrong answers, only efficient and effective answer
c)
3. Managers must apply sophisticated analysis techniques, such as Porter's strategies or forecasting, to make strategic decisions
d)
mathematical formulas placed in software that performs an analysis on a data set
143.
prejudice bias
a)
almost repetitive in nature
b)
a result of training data that is influenced by cultural or other stereotypes.
c)
an extension of goal-seeking analysis, finds the optimum value for a target variable by repeatedly changing other variables, subject to specified constraints
d)
3. Managers must apply sophisticated analysis techniques, such as Porter's strategies or forecasting, to make strategic decisions
144.
- the primary issue with prejudice bias is that the training data decisions consciously or unconsciously reflect cultural and social stereotypes.
a)
Bottom: Operational
b)
3. knowledge representation
c)
1. Transaction Processing System
d)
- the primary issue with prejudice bias is that the training data decisions consciously or unconsciously reflect cultural and social stereotypes.
145.
measurement bias
a)
a mathematical method of handling imprecise or subjective information
b)
managers develop overall business strategies, goals, and objectives as part of the company's strategic plan
c)
occurs when there is a problem with the data collected that skews the data in one direction.
d)
2. drill-down
146.
- can be avoided by collecting additional data using different devices.
a)
trends, sales, product statistics, and future growth projections
b)
- can be avoided by collecting additional data using different devices.
c)
Describes the original transaction record along with details such as its date, purpose, and amount spent and includes cash receipts, canceled checks, invoices, customer refunds, employee time sheet, etc.
d)
- Functioning without complete or well-structured information.
147.
variance bias
a)
sparkline
b)
2. Decision Support Systems
c)
stores large amounts of data with fast access
d)
a mathematical property of an algorithm.
148.
- the only bias not associated with the input or training data.
a)
- best suited to decision-making environments in which thousands or millions of solutions are possible.
b)
- the only bias not associated with the input or training data.
c)
2. drill-down
d)
bar chart
149.
neural network
a)
a category of AI that attempts to emulate the way the human brain works
b)
transferring information from one machine learning task to another
c)
- the reverse of what-if and sensitivity analysis.
d)
the aggregation of data from simple roll-ups to complex groupings of interrelated information
150.
use of neural network
a)
occurs when adding additional training examples by transforming existing examples
b)
haptic interface
c)
procedures
d)
analyze massive quantities of data to establish patterns and characteristics when the logic or rules are unknown
151.
neural networks features
a)
underfitting
b)
Encompasses all organizational information, and its primary purpose is to support the performing of managerial analysis tasks or semi-structured decisions
c)
- Learning and adjusting to new circumstances on their own.
d)
checks the impact of a change in a variable or assumption on the model.
152.
- Lending themselves to massive parallel processing.
a)
- Lending themselves to massive parallel processing.
b)
1. natural language processing
c)
schedules and budgets along with policies
d)
occurs when adding additional training examples by transforming existing examples
153.
- Functioning without complete or well-structured information.
a)
Weak AI
b)
employees are continuously evaluating company operations to hone the firm's abilities to identify, adapt to, and leverage change
c)
3. knowledge representation
d)
- Functioning without complete or well-structured information.
154.
- Coping with huge volumes of information with many dependent variables.
a)
- Coping with huge volumes of information with many dependent variables.
b)
analyze massive quantities of data to establish patterns and characteristics when the logic or rules are unknown
c)
bar chart
d)
- enable employees to move beyond reporting to using the information to directly increase business performance
155.
- Analyzing nonlinear relationships in information. (They have been called fancy regression analysis systems.)
a)
- Analyzing nonlinear relationships in information. (They have been called fancy regression analysis systems.)
b)
trends, sales, product statistics, and future growth projections
c)
They are the domain of operations managers, who are the closest to the customer.
d)
1. problem identification
156.
fuzzy logic
a)
a result of training data that is influenced by cultural or other stereotypes.
b)
tracks KPIs and CSFs by compiling information from multiple sources and tailoring it to meet user needs
c)
made frequently
d)
a mathematical method of handling imprecise or subjective information
157.
deep learning
a)
Encompasses all of the information contained within a single business process or unit of work, and its primary purpose is to support the performing of daily operational tasks
b)
a process that employs specialized algorithms to model and study complex datasets; the method is also used to establish relationships among data and datasets
c)
2. drill-down
d)
trends, sales, product statistics, and future growth projections
158.
reinforcement learning
a)
3. Managers must apply sophisticated analysis techniques, such as Porter's strategies or forecasting, to make strategic decisions
b)
arise in situations where established processes offer potential solutions
c)
The training of machine learning models to make a sequence of decisions
d)
the aggregation of data from simple roll-ups to complex groupings of interrelated information
159.
virtual reality
a)
A computer-simulated environment that can be a simulation of the real world or an imaginary world
b)
occuring in situations in which no procedures or rules exist to guide decision makers toward the correct choice.
c)
almost repetitive in nature
160.
augmented reality
a)
the viewing of the physical world with computer-generated layers of information added to it
b)
A type of artificial intelligence that enables computers to both understand concepts in the environment, and also to learn.
c)
a category of AI that attempts to emulate the way the human brain works
d)
Manipulation of information to create business intelligence in support of strategic decision making
161.
google glass
a)
a wearable computer with an optical head mounted display
b)
stores large amounts of data with fast access
c)
monitor the performance of organizational subunits
d)
checks the impact of a change in a variable or assumption on the model.
162.
virtual workplace
a)
- useful when users are uncertain about the assumptions made in estimating the value of certain key variables.
b)
1. Transaction Processing System
c)
finds the inputs necessary to achieve a goal such as a desired level of output.
d)
a work environment that is not located in any one physical space
163.
haptic interface
a)
4. pivot
b)
haptic interface
c)
- employees can react to information as soon as it becomes available and make decisions, solve problems, and change strategies daily instead of monthly
d)
a mathematical property of an algorithm.
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