CAP Data

Question 1

Line intercept sampling

Answer 1

Sampling method where elements in a region are selected if a chosen line segment (transect) intersects the element

Question 2

Theoretical sampling

Answer 2

Sample method where individuals are added to the sample based on results of data already collected

Question 3

Non-standard values data transformation

Answer 3

Identify categories represented by multiple categorical values and replace with a standard value

Question 4

Principal Component Analysis (PCA)

Answer 4

Dimensionality reduction method that uses orthogonal transformation to transform data set into a new coordinate system where first coordinate contains the most variance, second coordinate contains the second-most variance, etc.

Question 5

Data volume

Answer 5

The quantity of data stored in a warehouse

Question 6

probability proportionate to size sampling

Answer 6

Sample method where probability of an individual being chosen for the sample is proportional to the size of its subpopulation

Question 7

Smoothing data transformation

Answer 7

Apply a simple moving average or a LOESS regression to the data

Question 8

panel sampling

Answer 8

Sample method where individuals randomly chosen for an experiment are asked for information in waves of data collection

Question 9

Stratified sampling

Answer 9

Sample method where population is divided into subpopulations and individuals are randomly chosen for the sample from these subpopulations

Question 10

Binning data transformation

Answer 10

Divide the values of a continuous variable into discrete intervals

Question 11

Data strategy

Answer 11

A plan designed to improve the enterprise’s acquisition, storage, management, sharing, and use of data

Question 12

Statistical uncertainty

Answer 12

Natural randomness in a process that effects each experimental trial

Question 13

Voluntary sampling

Answer 13

Sample method where individuals choose to join the sample

Question 14

Skewness data transformation

Answer 14

Transform the distribution using a function such as a logarithm, a square root, or an inverse

Question 15

Normalization data transformation

Answer 15

Scaling the data to remove differences in magnitude between continuous variables; examples include min-max, z-scores, and decimal scaling

Question 16

Structured data

Answer 16

Information organized into a formatted repository so that its elements are easily searchable by basic algorithms

Question 17

Interval scale

Answer 17

Items in the scale are differentiated by degree of difference with no absolute zero as part of the scale

Question 18

Data value

Answer 18

The worth of data stored in and extracted from a warehouse

Question 19

Master data

Answer 19

Data objects agreed on and shared across the enterprise

Question 20

Precision of measurements

Answer 20

The closeness of agreement between independent measurements, primarily comes from random error

Question 21

Ratio scale

Answer 21

Items in the scale are differentiated by degree of difference and there is an absolute zero in the scale

Question 22

Data variety

Answer 22

The different forms of data contained in a warehouse

Question 23

Box-Cox Transformation

Answer 23

A method for transforming non-normal dependent variables into a normal shape

Question 24

Noisy data transformation

Answer 24

Use a smoothing function or funnel samples into bins

Question 25

Outlier data transformation

Answer 25

Apply a logarithm to the data or, if data is erroneous, discard from data set entirely

Question 26

Metadata

Answer 26

Data that provides information about other data

Question 27

Epistemic uncertainty

Answer 27

Randomness in a process due to things knowable in principle but not known while conducting an experiment

Question 28

Non-relational database

Answer 28

Database where data is not organized in a manner such that each row of information contains a unique key identifying the row

Question 29

Data veracity

Answer 29

The truthfulness and provenance of data contained in a warehouse

Question 30

Cluster sampling

Answer 30

Sample method where the population is divided into mutually homogeneous and internally heterogeneous subpopulations and a subpopulation is the sample (one-stage) or a simple random sample of a subpopulation is the sample (two-stage)

Question 31

Fitting data transformation

Answer 31

Find a function that describes common features of training and testing data, then apply function to that data; one such example is Fourier transformation

Question 32

Data velocity

Answer 32

The speed at which new data is added to the warehouse; the speed at which a user accesses existing data in the warehouse

Question 33

Data steward

Answer 33

Job role involving the use of organization's data governance processes to ensure fitness of data elements

Question 34

Nominal scale

Answer 34

Items in the scale are differentiated by name alone

Question 35

Design of Experiments (DOE)

Answer 35

An approach to problem solving involving the collection of data that supports valid, defensible, and supportable conclusions

Question 36

Ordinal scale

Answer 36

Items in the scale are differentiated by rank with no degree of difference between items specified

Question 37

Quota sampling

Answer 37

A non-probabilistic version of stratified sampling where judgment or convenience identifies what kinds of individuals are chosen for the sample

Question 38

Missing data transformation

Answer 38

Either replacing missing values with placeholder values, removing rows or columns with missing values, or using a statistical method to infer the missing value

Question 39

Simple random sampling

Answer 39

Sample method where every individual in the population has the same odds of being chosen for the sample

Question 40

relational database

Answer 40

Database based on organizing data into one or more tables of columns and rows where each row contains a unique key identifying the row

Question 41

Systematic sampling

Answer 41

Sample method where individuals are chosen for the sample from an ordered sampling frame; to be used only if population is homogenous

Question 42

Accidental sampling; convenience sampling

Answer 42

Non-probabilistic sample method where chosen individuals are readily available and convenient

Question 43

Data governance

Answer 43

Controls that ensure the data entry meets precise standards

Question 44

Accuracy

Answer 44

The agreement between independent measurements and the true value of what is measured, primarily comes from systematic error

Question 45

Unstructured data

Answer 45

Information that does not fit into pre-defined repository and is not organized in an easily searchable manner

Question 46

Snowball sampling

Answer 46

Sampling method where individuals already in the sample are asked to identify new individuals to add to the sample

Question 47

Data collection strategy

Answer 47

Iterative process of determining data needs, reviewing existing data, setting priorities for data, agreeing on roles and responsibilities for collecting the data, producing the data, and determining if data meets all needs

Question 48

Minimax sampling

Answer 48

Sample method where the sampling ratio does not follow the population statistics in order to ease binary classification tasks

Question 49

Response surface methodology (RSM)

Answer 49

A way to explore the relationships between explanatory variables and one or more response variables through a design of experiments

Question 50

Data privacy

Answer 50

The relationship between collection and dissemination of data, technology, public expectation of non-observation of collected data, and legal and political issues surrounding these issues