Four-class labels
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| Definition1
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| Definition2
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|---|---|---|---|---|
0 | 0 |
data analysis
|
where the researcher explains which analysis tools were selected and why they were the best fit for the general research questions asked and the specific data collection methods employed
|
looking at the data to understand its meaning and how it might support our hypothesis
|
0 | 0 |
data analysis
|
the manipulation of collected data so that the development team members who are participating in systems analysis can use the data
|
performing analysis and understanding results: machine learning, computational statistics, visualisation, ...
|
0 | 0 |
data analysis
|
after experimentation, data is displayed using a graph to show patterns/trends. be organized.. title, units labels, variables
|
describing data using graphs and numbers.
|
0 | 0 |
data analysis
|
*organize data to show trends, *develop graphs of data, *show all mathematical calculations with units, *apply any statistical analysis, *summarize results.
|
the process of evaluating data using analytical and logical reasoning; often involves putting numerical values into picture form, such as bar graphs, line graphs, and circle graphs.
|
0 | 0 |
data analysis
|
where the researcher explains which analysis tools were selected and why they were the best fit for the general research questions asked and the specific data collection methods employed
|
threat to internal validity caused by how data is analyzed. it must be analyzed correctly. appropriate statistical techniques must be used.
|
0 | 0 |
data analysis
|
tableau has an ever growing set of analytical functions that allow you to dive deep into understanding complex relationships, patterns, and correlations in the data
|
analyze results, communicate findings, use findings for program improvement.
|
0 | 0 |
data analysis
|
threat to internal validity caused by how data is analyzed. it must be analyzed correctly. appropriate statistical techniques must be used.
|
applying statistics and logic techniques to define, illustrate, and evaluate data
|
1 | 0 |
data analysis
|
*organize data to show trends, *develop graphs of data, *show all mathematical calculations with units, *apply any statistical analysis, *summarize results.
|
the process of interpreting the meaning of data collected in an experiment, finding patterns in the data, and thinking about what the patterns mean.
|
2 | 1 |
data analysis
|
looking at the data to understand its meaning and how it might support our hypothesis
|
consists of the strategies and methods that makes sense of the data to answer the research problem and questions.
|
0 | 0 |
data analysis
|
the process of placing observations in numerical form and manipulating them according to their arithmetic properties to derive meaning from them
|
refers to deriving some meaning from the observations made during a research project.
|
0 | 0 |
data analysis
|
is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making.
|
analyze results, communicate findings, use findings for program improvement.
|
0 | 0 |
data analysis
|
threat to internal validity caused by how data is analyzed. it must be analyzed correctly. appropriate statistical techniques must be used.
|
comparison of what is logically expected with what is actually observed or using observations to develop a new set of logic
|
3 | 1 |
data analysis
|
transform inputs into outputs (such as data summarization or regression analysis)
|
functions transform inputs into outputs, including simple summarization to complex mathematical modeling
|
1 | 0 |
data analysis
|
record observations and analyze what the data means. often, you'll prepare a table or graph of the data.
|
- make hypotheses - look for what is not there - scrutinize for the obvious - keep your mind open - trust the data - watch the &"n&"
|
1 | 0 |
data analysis
|
helps distinguish among multiple working hypothesis. one of the first steps toward determining whether an observed pattern has validity
|
the process of interpreting the meaning of data collected in an experiment, finding patterns in the data, and thinking about what the patterns mean.
|
2 | 1 |
data analysis
|
looking at the data to understand its meaning and how it might support our hypothesis
|
threat to internal validity caused by how data is analyzed. it must be analyzed correctly. appropriate statistical techniques must be used.
|
0 | 0 |
data analysis
|
- make hypotheses - look for what is not there - scrutinize for the obvious - keep your mind open - trust the data - watch the &"n&"
|
helps distinguish among multiple working hypothesis. one of the first steps toward determining whether an observed pattern has validity
|
0 | 0 |
data analysis
|
process, perception, and outcome data can all be analyzed and later reported -focuses on organizing and summarizing collected information into themes or statistical descriptions -involves stakeholders from the beginning
|
phase in which the nurse examines and groups the data collected to make nursing judgments . the end result is formulation of nursing diagnosis, collaborative problems and/or referrals
|
1 | 0 |
data analysis
|
performing analysis and understanding results: machine learning, computational statistics, visualisation, ...
|
submission of data to statistical analysis; includes sorting into categories and determining relationships between variables.
|
1 | 0 |
data analysis
|
is the process of examining and transforming data in order to summarize a situation, highlight useful information, discover relationships, and suggest conclusions
|
analyze results, communicate findings, use findings for program improvement.
|
2 | 1 |
data analysis
|
is the processing of data collected during the course of a study to identify trends and patterns of relationships
|
performing analysis and understanding results: machine learning, computational statistics, visualisation, ...
|
2 | 1 |
data analysis
|
the task of transforming, summarizing, or modeling data to allow the user to make meaningful conclusions
|
makes sense of an organization's collected data and turn it into useful information and validate their future decisions.
|
0 | 0 |
data analysis
|
using software tools to evaluate digital data so you can use the information in meaningful ways.
|
is the process of examining and transforming data in order to summarize a situation, highlight useful information, discover relationships, and suggest conclusions
|
1 | 0 |
data analysis
|
consists of the strategies and methods that makes sense of the data to answer the research problem and questions.
|
applying statistics and logic techniques to define, illustrate, and evaluate data
|
1 | 0 |
data analysis
|
comparison of what is logically expected with what is actually observed or using observations to develop a new set of logic
|
applying statistics and logic techniques to define, illustrate, and evaluate data
|
2 | 1 |
data analysis
|
is the processing of data collected during the course of a study to identify trends and patterns of relationships
|
submission of data to statistical analysis; includes sorting into categories and determining relationships between variables.
|
1 | 0 |
data analysis
|
the task of transforming, summarizing, or modeling data to allow the user to make meaningful conclusions
|
analyze results, communicate findings, use findings for program improvement.
|
1 | 0 |
data analysis
|
the task of transforming, summarizing, or modeling data to allow the user to make meaningful conclusions
|
tableau has an ever growing set of analytical functions that allow you to dive deep into understanding complex relationships, patterns, and correlations in the data
|
2 | 1 |
data analysis
|
organizing and interpreting the data and observations to figure out what it means
|
reviewing the data collected to look for patterns or inferences that can be determined
|
1 | 0 |
data analysis
|
submission of data to statistical analysis; includes sorting into categories and determining relationships between variables.
|
the process of compiling, analyzing, and interpreting the results of primary and secondary data collection.
|
1 | 0 |
data analysis
|
is a process of inspecting, cleaning, transforming, and modeling data with the goal of discovering useful information, suggesting conclusions, and supporting decision-making.
|
using software tools to evaluate digital data so you can use the information in meaningful ways.
|
0 | 0 |
data analysis
|
using software tools to evaluate digital data so you can use the information in meaningful ways.
|
analyze results, communicate findings, use findings for program improvement.
|
1 | 0 |
data analysis
|
is the process of examining and transforming data in order to summarize a situation, highlight useful information, discover relationships, and suggest conclusions
|
makes sense of an organization's collected data and turn it into useful information and validate their future decisions.
|
1 | 0 |
data analysis
|
transform inputs into outputs (such as data summarization or regression analysis)
|
functions transform inputs into outputs, including simple summarization to complex mathematical modeling such as regression analysis
|
1 | 0 |
data analysis
|
crunching the numbers to see if they support predictions
|
looking at the data to understand its meaning and how it might support our hypothesis
|
1 | 0 |
data analysis
|
tableau has an ever growing set of analytical functions that allow you to dive deep into understanding complex relationships, patterns, and correlations in the data
|
is the process of examining and transforming data in order to summarize a situation, highlight useful information, discover relationships, and suggest conclusions
|
0 | 0 |
data analysis
|
where the researcher explains which analysis tools were selected and why they were the best fit for the general research questions asked and the specific data collection methods employed
|
comparison of what is logically expected with what is actually observed or using observations to develop a new set of logic
|
1 | 0 |
data analysis
|
*organize data to show trends, *develop graphs of data, *show all mathematical calculations with units, *apply any statistical analysis, *summarize results.
|
various techniques to summarize and examine the collected data to help determine trends and relationships among the variables
|
2 | 1 |
data analysis
|
the task of transforming, summarizing, or modeling data to allow the user to make meaningful conclusions
|
using software tools to evaluate digital data so you can use the information in meaningful ways.
|
1 | 0 |
data analysis
|
tableau has an ever growing set of analytical functions that allow you to dive deep into understanding complex relationships, patterns, and correlations in the data
|
using software tools to evaluate digital data so you can use the information in meaningful ways.
|
0 | 0 |
data analysis
|
the process of evaluating data using analytical and logical reasoning; often involves putting numerical values into picture form, such as bar graphs, line graphs, and circle graphs.
|
- make hypotheses - look for what is not there - scrutinize for the obvious - keep your mind open - trust the data - watch the &"n&"
|
1 | 0 |
data analysis
|
analyses are techniques or statistical tools designed to aid in describing and summarizing findings, helping researchers to draw reasonable conclusions from the data
|
an objective report of the summary of measures that best meet assumptions about data.
|
2 | 1 |
data analysis
|
-must account for variables outside of the independent and dependent variables considered (age, gender, smoking status, bmi, and other factors)
|
must account for variables outside of the independent and dependent variable some can be -confounding: unexpected factors in the experiment
|
2 | 1 |
data analysis
|
various techniques to summarize and examine the collected data to help determine trends and relationships among the variables
|
the process of interpreting the meaning of data collected in an experiment, finding patterns in the data, and thinking about what the patterns mean.
|
0 | 0 |
data analysis
|
*organize data to show trends, *develop graphs of data, *show all mathematical calculations with units, *apply any statistical analysis, *summarize results.
|
helps distinguish among multiple working hypothesis. one of the first steps toward determining whether an observed pattern has validity
|
2 | 1 |
data analysis
|
crunching the numbers to see if they support predictions
|
applying statistics and logic techniques to define, illustrate, and evaluate data
|
0 | 0 |
data analysis
|
the process of evaluating data using analytical and logical reasoning; often involves putting numerical values into picture form, such as bar graphs, line graphs, and circle graphs.
|
helps distinguish among multiple working hypothesis. one of the first steps toward determining whether an observed pattern has validity
|
0 | 0 |
data analysis
|
a process of modifying data in order to find information.
|
-when analyzing data to estimate the strength of an association between variables, first determine the type of data at hand.
|
1 | 0 |
data analysis
|
performing analysis and understanding results: machine learning, computational statistics, visualisation, ...
|
the process of compiling, analyzing, and interpreting the results of primary and secondary data collection.
|
2 | 1 |
data analysis
|
the process of evaluating data using analytical and logical reasoning; often involves putting numerical values into picture form, such as bar graphs, line graphs, and circle graphs.
|
various techniques to summarize and examine the collected data to help determine trends and relationships among the variables
|
2 | 1 |
data analysis
|
record observations and analyze what the data means. often, you'll prepare a table or graph of the data.
|
the process of evaluating data using analytical and logical reasoning; often involves putting numerical values into picture form, such as bar graphs, line graphs, and circle graphs.
|
0 | 0 |
data analysis
|
consists of the strategies and methods that makes sense of the data to answer the research problem and questions.
|
comparison of what is logically expected with what is actually observed or using observations to develop a new set of logic
|
2 | 1 |
data analysis
|
using software tools to evaluate digital data so you can use the information in meaningful ways.
|
makes sense of an organization's collected data and turn it into useful information and validate their future decisions.
|
1 | 0 |
data analysis
|
is the processing of data collected during the course of a study to identify trends and patterns of relationships
|
the manipulation of collected data so that the development team members who are participating in systems analysis can use the data
|
1 | 0 |
data analysis
|
run statistical tests to answer the aim/objective, question, hypothesis
|
describe the sample answer the research question and or test hypothesis consider post-hoc analysis as appropriate
|
0 | 0 |
data analysis
|
crunching the numbers to see if they support predictions
|
threat to internal validity caused by how data is analyzed. it must be analyzed correctly. appropriate statistical techniques must be used.
|
1 | 0 |
data analysis
|
crunching the numbers to see if they support predictions
|
comparison of what is logically expected with what is actually observed or using observations to develop a new set of logic
|
0 | 0 |
data analysis
|
threat to internal validity caused by how data is analyzed. it must be analyzed correctly. appropriate statistical techniques must be used.
|
consists of the strategies and methods that makes sense of the data to answer the research problem and questions.
|
0 | 0 |
data analysis
|
where the researcher explains which analysis tools were selected and why they were the best fit for the general research questions asked and the specific data collection methods employed
|
applying statistics and logic techniques to define, illustrate, and evaluate data
|
0 | 0 |
data analysis
|
where the researcher explains which analysis tools were selected and why they were the best fit for the general research questions asked and the specific data collection methods employed
|
crunching the numbers to see if they support predictions
|
1 | 0 |
data analysis
|
looking at the data to understand its meaning and how it might support our hypothesis
|
comparison of what is logically expected with what is actually observed or using observations to develop a new set of logic
|
2 | 1 |
data analysis
|
describes the sample, answers the research question and/or tests the hypothesis
|
describe the sample answer the research question and or test hypothesis consider post-hoc analysis as appropriate
|
0 | 0 |
data analysis
|
is the processing of data collected during the course of a study to identify trends and patterns of relationships
|
the process of compiling, analyzing, and interpreting the results of primary and secondary data collection.
|
0 | 0 |
data analysis
|
various techniques to summarize and examine the collected data to help determine trends and relationships among the variables
|
helps distinguish among multiple working hypothesis. one of the first steps toward determining whether an observed pattern has validity
|
0 | 0 |
data analysis
|
record observations and analyze what the data means. often, you'll prepare a table or graph of the data.
|
*organize data to show trends, *develop graphs of data, *show all mathematical calculations with units, *apply any statistical analysis, *summarize results.
|
0 | 0 |
data analysis
|
record observations and analyze what the data means. often, you'll prepare a table or graph of the data.
|
helps distinguish among multiple working hypothesis. one of the first steps toward determining whether an observed pattern has validity
|
3 | 1 |
data analysis
|
run statistical tests to answer the aim/objective, question, hypothesis
|
describes the sample, answers the research question and/or tests the hypothesis
|
1 | 0 |
query optimization
|
examining multiple ways of executing the same query and choosing the fastest option
|
parallel query processing-possible when working in multiprocessor systems overriding automatic query optimization-allows for query writers to preempt the automated optimization
|
1 | 0 |
query optimization
|
parallel query processing-possible when working in multiprocessor systems overriding automatic query optimization-allows for query writers to preempt the automated optimization
|
minimizing response times for actions by choosing the most efficient query to achieve it
|
0 | 0 |
query optimization
|
to minimize response times for large, complex queries
|
restructure physical view to optimize response times to queries delete unused data
|
2 | 1 |
query optimization
|
examining multiple ways of executing the same query and choosing the fastest option
|
minimizing response times for actions by choosing the most efficient query to achieve it
|
0 | 0 |
environmental conditions
|
abiotic environmental factors that vary in space and time and to which organisms are differentially responsive
|
the state of the environment
|
0 | 0 |
environmental conditions
|
how fabric reacts to exposure and storage
|
the state of the environment
|
0 | 0 |
environmental conditions
|
abiotic environmental factors that vary in space and time and to which organisms are differentially responsive
|
weather, wildfire in progress, daily fire potential index
|
0 | 0 |
data centers
|
storage management consume alot of energy, &" server farms&"
|
industrial facilities whose sole purpose is the storage and management of external data - &"server farms&" - normally require minimal architecture and few employees - consume significant energy
|
0 | 0 |
data centers
|
storage management consume alot of energy, &" server farms&"
|
industrial facilities whose sole purpose is the storage and management of external data, also called &"data farms&"
|
0 | 0 |
data centers
|
large numbers of network serves used for the storage, processing, management, distribution, and archiving of data, systems. web traffic, services, and enterprise applications.
|
a facility used to house management information systems and associated components, such as telecommunications and storage systems
|
0 | 0 |
data centers
|
large amounts of data dedicated space to store data servers: host applications and content for use clients: consume hosted resources peers: work together to share data
|
a facility used to house management information systems and associated components, such as telecommunications and storage systems
|
2 | 1 |
data centers
|
industrial facilities whose sole purpose is the storage and management of external data - &"server farms&" - normally require minimal architecture and few employees - consume significant energy
|
industrial facilities whose sole purpose is the storage and management of external data, also called &"data farms&"
|
0 | 0 |
information flow
|
the structure and speed of messages between individuals and or organizations
|
one of the most important differences between large and small groups
|
0 | 0 |
information flow
|
the structure and speed of messages between individuals and or organizations
|
-who performs the task, with what indications and with what feedback -specifies the communication between people and the interactions between people and technology
|
0 | 0 |
information flow
|
'marked clauses'- manipulated sentences,unusual, don't always follow svo want to highlight something what is considered most important what is assumed the audience already know
|
the movement of information from category to another. think of a highly classified file being copied and made available to an unclassified audience.
|
0 | 0 |
information flow
|
-each class is assigned a security classification with clearances -has compartments (dedicated, multilevel, compartmented) -&"multi-level security policies&"
|
the illicit transmission of information without leakage of rights
|
0 | 0 |
information flow
|
-who performs the task, with what indications and with what feedback -specifies the communication between people and the interactions between people and technology
|
one of the most important differences between large and small groups
|
0 | 0 |
recommender systems
|
used when user doesn't know what they want i.e. netflix
|
noisy data, commercial pay-off (e.g. amazon, netflix)
|
2 | 1 |
recommender systems
|
web-based information filtering system that takes the inputs from users and then uses the inputs to provide recommendations for other users
|
web-based information filtering system that takes the inputs from users and then aggregates the inputs to provide recommendations for other users in their product or service selection choices
|
2 | 1 |
data distribution
|
the overall shape of a graph which shows the way in which data are spread out or clustered together
|
this can be described by: the measure of center, spread, and overall shape.
|
2 | 1 |
data distribution
|
list of all possible values and how often they occur
|
the frequency distribution of individual values in a data set.
|
2 | 1 |
data distribution
|
listing all possible values obtained in the data & how often they occurred
|
the frequency distribution of individual values in a data set.
|
2 | 1 |
data distribution
|
list of all possible values and how often they occur
|
what data occurred and how often (table, graph, list, etc)
|
1 | 0 |
data distribution
|
uni variate data only! mean, median, modality, skewness, symmetry, unusual values, shape
|
the overall shape of a graph which shows the way in which data are spread out or clustered together
|
3 | 1 |
data distribution
|
listing all possible values obtained in the data & how often they occurred
|
list of all possible values and how often they occur
|
3 | 1 |
data distribution
|
the overall shape of a graph; can be skewed right, symmetric, or skewed left.
|
the overall shape of a graph which shows the way in which data are spread out or clustered together
|
2 | 1 |
data distribution
|
what data occurred and how often (table, graph, list, etc)
|
the frequency distribution of individual values in a data set.
|
1 | 0 |
data distribution
|
the overall shape of a graph; can be skewed right, symmetric, or skewed left.
|
this can be described by: the measure of center, spread, and overall shape.
|
2 | 1 |
data distribution
|
-what data occurred -how often -ex: table, graph, etc
|
a list or graph that shows what values happened and how often
|
1 | 0 |
data distribution
|
the overall shape of a graph; can be skewed right, symmetric, or skewed left.
|
uni variate data only! mean, median, modality, skewness, symmetry, unusual values, shape
|
0 | 0 |
data distribution
|
uni variate data only! mean, median, modality, skewness, symmetry, unusual values, shape
|
this can be described by: the measure of center, spread, and overall shape.
|
0 | 0 |
reference model
|
a model that is part of a dssa to describe the context and domain semantics important to understand a reference architecture and its architectural decisions
|
provide a means of information about that class of system and of comparing different architectures
|
1 | 0 |
reference model
|
every variable refers to the same object in memory and assignment means making the left refer to the same object as is on the right
|
a named reference to a value platonic: only one value
|
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