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Data Management > FINAL > Flashcards

FINAL Flashcards

1
Q

The process of inspecting, organizing, measuring, and modeling data to make statistically sound decisions.

A

Data Analysis

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2
Q

The strategy of turning information into insight and developing conclusive, fact-based strategies to gain competitive edge.

A

Analytics

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3
Q

Analytics that depict and describe the characteristics of what has happened in the past.

A

Descriptive Analytics

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4
Q

Analytics that use data from the past to predict the future.

A

Predictive Analytics

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5
Q

Analytics that use experimental design and optimization to suggest a course of action.

A

Prescriptive Analytics

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6
Q

Standards or points-of-reference for an industry or sector that can be used for comparison and evaluation.

A

Benchmarks

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7
Q

Describes a massive volume of data so large it’s difficult to process using traditional database and software techniques.

A

Big Data

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8
Q

The process of searching customer data in order to detect patterns to guide marketing decisions.

A

Data Mining

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9
Q

Data that can lie along any point in a range of data and is classified as either interval or ratio.

A

Continuous Data

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10
Q

A continuous data type where objects are an equal interval apart and then value ‘zero’ does NOT represent the absence of a measured value.

A

Interval Data

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11
Q

A continuous data type where objects are an equal interval apart and the value ‘zero’ DOES represent the absence of a measured property and where the values can be multiples of one another.

A

Ratio Data

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12
Q

Data that can only take on whole values and has clear boundaries that can be classified as either nominal or ordinal.

A

Discrete Data

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13
Q

A discrete data type that places objects into discrete, unordered categories.

A

Nominal Data

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14
Q

A discrete data type that places objects into discrete, ordered categories, with higher order indicating more of that quality.

A

Ordinal Data

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15
Q

The extent or degree of statistical association among two or more variables.

A

Correlation

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16
Q

The set of practices undertaken to ensure an organization provides and maintains high-quality information through the cleaning, organizing, and repairing of data.

A

Data Quality Management

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17
Q

An error that occurs when information is missing from a data set.

A

Omission Error

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18
Q

Errors in measurement caused by unpredictable statistical fluctuations.

A

Random Errors

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19
Q

Errors in measurement that are constant and can be caused by faulty equipment or bias.

A

Systematic Errors

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20
Q

A strategy that consists of observational and experimental studies to help guide a study in a coherent and logical manner.

A

Research Design

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21
Q

Studies conducted in a natural environment where the variables are not completely controlled by the researcher.

A

Observational Studies

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22
Q

Studies in which all variable measurements and manipulations are under the researcher’s control.

A

Experimental Studies

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23
Q

A study that observes people going forward in-time from the moment of their entry into the study.

A

Prospective Cohort Study

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24
Q

A bias that is introduced during the sample of the study, when the sample is not representative of the population.

A

Selection Bias

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25
Q

A bias that occurs when members of the population choose not to participate in the study.

A

Response Bias

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26
Q

A straight-forward and commonly used sampling method in which a sample selected from a population has an equal opportunity to be chosen.

A

Simple Random Sample

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27
Q

A bias that occurs when an assumption is made that has not yet been proven.

A

Unfounded Assumption

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28
Q

The relationship of cause and effect.

A

Causation

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29
Q

An outcome, or set of outcomes, whose chance of occurrence is represented by probability.

A

Event

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30
Q

The occurrence of an event not happening.

A

Complement

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31
Q

The probability of two events happening where elements of both events meet.

A

Intersection

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32
Q

When two or more events are not able to occur at the same time.

A

Mutually Exclusive

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33
Q

A visual representation of mathematical sets of events.

A

Venn Diagram

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34
Q

The chance of an event occurring where ‘zero’ indicates no chance of an event and ‘one’ indicates that an event will happen.

A

Probability

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35
Q

The probability of an event occurring, given that another event has already occurred.

A

Conditional Probability

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36
Q

The number of unique, ordered possibilities for a certain situation.

A

Permutations

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37
Q

The number of different, unordered possibilities for a certain situation.

A

Combinations

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38
Q

The ratio of the number of occurrences of an event compared to the overall possible occurrences of that event.

A

Frequency

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39
Q

The average, calculated by adding a series of values in a dataset together and dividing it by the total number in the series of the data.

A

Mean

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40
Q

The value of the quantity lying at the midpoint of a frequency distribution.

A

Median

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41
Q

The highest frequency of any specific event.

A

Mode

42
Q

A score calculated by subtracting the mean from and individual score.

A

Deviation Score

43
Q

A measure of the spread of dispersion of a data set. The closer the data to the mean, the smaller the variance.

A

Variance

44
Q

The square root of the variance, a measure of how spread out the numbers are in a set of data.

A

Standard Deviation

45
Q

A statistical measure that indicates the number of standard deviations a data point is from the mean.

A

Z-Score

46
Q

A graph that displays continuous data.

A

Histogram

47
Q

A graph that measures the distribution of data over discrete groups of categories.

A

Bar Chart

48
Q

A graphic that uses dots to show relationships or correlations between variables.

A

Scatter (Plot) Diagram

49
Q

A statistical analysis commonly used to compare the difference between two groups; specifically, to determine if two means are different from one another.

A

T-Test

50
Q

A hypothesis test that is used to compare a sample mean to a known value, often a population mean.

A

One-Sample T-Test

51
Q

A common hypothesis test that is used to determine the distribution of categorical data.

A

Chi-Squared Test

52
Q

A variance analysis method that analyzes the difference between a particular variable and multiple populations (three or more means).

A

ANOVA Analysis

53
Q

One value used to test the hypothesis; it is a numerical summary of the data set.

A

Test Statistic

54
Q

The tipping point between a test statistic value that causes one to reject the null hypothesis and one that indicates that one should fail to reject the null hypothesis.

A

Critical Value

55
Q

A statistical analysis tool that quantifies the relationship between a dependent variable and one or more independent variables; commonly used for cost behavior and forecasting sales.

A

Regression Analysis

56
Q

A regression analysis that uses time as the independent variable and is used for evaluating patterns in data to make decisions about inventory or staffing levels.

A

Time-Series Analysis

57
Q

A regression analysis that arranges terms or values based on different variables into “natural” groups. It is commonly used for understanding the make-up of an industry’s different areas.

A

Cluster Analysis

58
Q

A regression analysis with only one independent variable.

A

Simple Linear Regression

59
Q

A regression analysis of how multiple independent variables affect one dependent variable.

A

Multiple Linear Regression

60
Q

A business management system that focuses on product and service quality and the means to achieve it.

A

Quality Management

61
Q

A process that monitors the quality of operations and is reactive to problems.

A

Quality Control

62
Q

A process that is responsible for providing assurance that products and services are consistently maintained at a high level of quality and is proactive to problems.

A

Quality Assurance

63
Q

A business management system aimed at translating the organization’s strategic goals into a set of performance objectives using financial, internal, innovative, and customer/stakeholder input.

A

Balanced Scorecard

64
Q

A business process that focuses on eliminating anything that does not add value for customers.

A

Lean Processes

65
Q

A four step process for testing hypotheses and solving problems.

A

Plan-Do-Check-Act Cycle

66
Q

A quantifiable performance measurement that demonstrates how effectively an organization is achieving key business objectives.

A

Key Performance Indicators (KPI)

67
Q

A tool used to unite key performance data sources and provide at-a-glance visual feedback.

A

KPI Dashboard

68
Q

A quality management diagram that defines the boundaries of a process and shows how it’s suppliers, inputs, products, outputs, and customers affect quality.

A

SIPOC Diagram

69
Q

A process control that helps teams ensure that work processes are working to the best of their ability.

A

Statistical Process Control (SPC)

70
Q

Measurements that allow people to gauge results effectively.

A

Metrics

71
Q

The process of selecting research participants or survey respondents of a population.

A

Sampling

72
Q

Data that shows whether a result meets a requirement and is yes/no or pass/fail in nature.

A

Attributable Data

73
Q

Data that shows how well a result meets a requirement, often shown on a scale or as a rating.

A

Variable Data

74
Q

Variation that occurs as a natural part of a process.

A

Common Cause Variation

75
Q

Abnormal variation that is not part of a natural process.

A

Special Cause Variation

76
Q

A best practice process that includes run and control charts, cause-and-effect diagrams, flowcharts, check sheets, histograms, bar charts, Pareto charts, and scatter diagrams.

A

Ishikawa’s Seven Basic Tools of Quality

77
Q

A line chart that shows performance measurements over time and can help users uncover trends or aberrations in processes.

A

Run Chart

78
Q

A modified run chart that also provides upper and lower control limits that a process should not exceed.

A

Control Chart

79
Q

A quality management diagram that shows the underlying causes of a problem or event; also known as a fishbone diagram.

A

Cause-And-Effect Diagram

80
Q

A graphical representation of the steps that make up a process.

A

Flowchart

81
Q

A structured form or table that allows users to collect and record data in a simple format; usually by placing check marks next to recordable units.

A

Check Sheet

82
Q

A graph that displays continuous data with vertical bars showing counts or numbers in each range of data.

A

Histogram

83
Q

A graph that measures the distribution of data over discrete groups and/or categories.

A

Bar Chart

84
Q

A histogram that or ordered by the frequency of occurrence, showing how many results were generated by each identifiable cause.

A

Pareto Chart

85
Q

A graphic that uses dots to show relationships or correlations between variables.

A

Scatter (Plot) Diagram

86
Q

Business processes that focus on eliminating anything that doesn’t add value for customers.

A

Lean Processes

87
Q

A lean process of producing and delivering products and services exactly when a customer needs them.

A

Just-In-Time Inventory

88
Q

All of the steps, processes, and communication involved in the production of goods and services.

A

Value Stream

89
Q

A highly-disciplined, data-driven approach for improving quality by using statistical analysis to identify and eliminate defects.

A

Six Sigma

90
Q

Quality attributes that customers and stakeholders feel are most important and are used by these groups to evaluate the quality of process results.

A

Critical-To-Quality Characteristics (CTQs)

91
Q

A diagram that breaks customer needs and expectations down into values that can be measured and monitored.

A

CTQ Tree Diagram

92
Q

A management strategy that uses results as the central measurement of performance that involves five stages: input, activities, output, outcome, and impact.

A

Results-Based Management (RBM)

93
Q

An analysis that is used to see if funding a project is worth the outcome of the project.

A

Cost-Benefit Analysis

94
Q

Tests that compare an individual to other individuals.

A

Norm-Referenced Tests

95
Q

Tests that compare an individual to certain defined standards.

A

Criterion-Referenced Tests

96
Q

The actual score an individual achieves on a test

A

Observed Score

97
Q

The average score an individual would achieve if they were to take a test infinite times.

A

True Score

98
Q

Errors in measurement caused by unpredictable statistical fluctuations.

A

Random Measurement Errors

99
Q

Errors in measurement that are constant within a specified dataset and can be caused by faulty equipment or bias.

A

Systematic Measurement Error

100
Q

A theory that states that in a test without systematic error, the observed score is the true score plus the random error.

A

True Score Theory

101
Q

A model of scoring that focuses on analysis of each question’s answer and is often more useful that classical test theory.

A

Item Response Theory (IRT)

Data Management (1 decks)

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