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WGU C207 DATA-DRIVEN DECISION MAKING OBJECTIVE ASSESSMENT DETAILED QUESTIONS AND ANSWERS

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WGU C207 DATA-DRIVEN DECISION MAKING OBJECTIVE ASSESSMENT DETAILED QUESTIONS AND ANSWERS

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WGU C207
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WGU C207









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WGU C207
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31 augustus 2025
Aantal pagina's
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Geschreven in
2025/2026
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WGU C207 DATA-DRIVEN DECISION MAKING
OBJECTIVE ASSESSMENT DETAILED QUESTIONS AND
ANSWERS
Activities (RBM stage) - ANSWER: second step involves the process that converts
inputs to outputs (actions necessary to produces results - training, evaluating,
developing)

Alternative hypothesis - ANSWER: The argument that either a sample is not equal to,
greater than, or less than the hypothesized null sample

Analysis of Variance (ANOVA) - ANSWER: a technique used to determine if there is
a sufficient evidence from sample data of three or more populations to conclude that the
means of the population are not all equal

Analytics - ANSWER: The discovery, analysis, and communication of meaningful
patterns in data.

Autocorrelation - ANSWER: A relationship between two variables that is inherently
non-linear

Balanced Scorecard - ANSWER: An approach using multiple measures to evaluate
performance, including financial measures, and the non-financial measures of
customers, internal business processes, and learning and growth.

Bar chart - ANSWER: A graph that measures the distribution of data over discrete
groups or categories.

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

Big Data - ANSWER: very large amounts of data; an all-encompassing term for any
collection of data sets so large and complex that it becomes difficult to process them #$%^&%
using traditional data processing applications $%^&%$
%^&&^%
Blind Study - ANSWER: A study performed where the participants are not told if they
$%^&*(&
are in the treatment group or control group
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body mass index (BMI) - ANSWER: A measure, based on a person's weight and &*(*&^%
height, that is used to classify people as underweight or overweight. $#$%^&
(*&^%$%
Business process - ANSWER: A sequence of logically related and time based work ^&*(*&^
activities to provide a specific output for a customer.
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, WGU C207 DATA-DRIVEN DECISION MAKING
OBJECTIVE ASSESSMENT DETAILED QUESTIONS AND
ANSWERS
Central Limit Theorem - ANSWER: A theorem that states that, the greater the
sample, the closer the mean of the sample is to the entire population and the more the
results will look like a normal distribution

Cluster Analysis - ANSWER: The process of arranging terms or values based on
different variables into "natural" groups

Cointegration - ANSWER: Occurs when two time series are moving with a common
pattern due to a connection between the two time series

Combination - ANSWER: The number of different unordered possibilities for a certain
situation.

Complement - ANSWER: The occurrence of an event not happening, the opposite

Confidence interval - ANSWER: An interval estimate used to indicate reliability

Continuous Data - ANSWER: Data that can lay along any point in a range of data

Control chart - ANSWER: A graphic display of process data over time and against
established control limits, and that has a centerline that assists in detecting a trend of
plotted values toward either control limit.

Control limits - ANSWER: The area composed of three standard deviations on either
side of the centerline, or mean, of a normal distribution of data plotted on a control chart
that reflects the expected variation in the data

Criterion-reference test - ANSWER: compare an individual to certain defined
standards #$%^&%
$%^&%$
Critical Success Factors - ANSWER: The important things an entity must do to be %^&&^%
successful, such as quality measures, customer service, or efficiency. $%^&*(&
^%$#%^
Cumulative Average-Time Learning Model - ANSWER: A learning curve model in
&*(*&^%
which the cumulative average time per unit declines by a constant percentage each
time the cumulative quantity of units produced is doubled $#$%^&
(*&^%$%
Cumulative distributions - ANSWER: The probability that a random variable will be ^&*(*&^
found at a value less than or equal to a given number %$%^&*
)(*&^%$
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