Four-class labels
int64 0
3
| Binary labels
int64 0
1
| Entity
stringlengths 8
33
| Definition1
stringlengths 15
259
| Definition2
stringlengths 14
253
|
|---|---|---|---|---|
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 |
Subsets and Splits