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WGU C207 EXAM & PRE-ASSESSMENT Q&A | 500 PRACTICE QUESTIONS |

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Prepare for WGU C207 Data-Driven Decision Making with this comprehensive study guide featuring 500 practice questions and detailed answers covering both the Objective Assessment (OA) and Pre-Assessment (PA). Review descriptive and inferential statistics, hypothesis testing, probability, regression analysis, data interpretation, sampling methods, confidence intervals, data visualization, business analytics, evidence-based decision-making, and quantitative research concepts. Ideal for WGU students preparing for the C207 course assessments.

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WGU C207 ACTUAL EXAM AND PRE-ASSESSMENT
EXAM |COMPLETE 500 QUESTIONS WITH
DETAILED VERIFIED CORRECT ANSWERS |PRE-
EVALUATED A+




Random Errors - ANSWER-Error in measurement caused by unpredictable statistical fluctuations



Information Bias - ANSWER-A prejudice in the data that results when either the respondent or the
interviewer has an agenda and is not presenting impartial questions or responding with truly honest
responses, respectively



Ratio Data - ANSWER-Similar to interval data in that the data is ordered within a range and with each
data point being an equal interval apart, also has a natural zero point which indicates none of the given
quality



Data Set - ANSWER-A collection of related data records on a storage device.

,Nominal Data - ANSWER-Sometimes called categorical data or qualitative data, this data type is used to
label subjects or data by name



Reliable Data - ANSWER-Data that is consistent and repeatable



Davenport-Kim Three Stages Model - ANSWER-A decision-making model developed by Thomas
Davenport and Jinho Kim that consists of three stages:

Framing the problem

Solving the problem

Communicating the problem



Blind study - ANSWER-A study performed where the participants are not told if they are in the
treatment group or control group



Double-Blind Study - ANSWER-A study performed where neither the treatment allocators nor the
participant knows which group the participant is in



Measurement Bias - ANSWER-A prejudice in the data that results when the sample is not representative
of the population being represented.



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



Data Management - ANSWER-The management, including the cleaning and storage, of collected data



Triple-Blind Study - ANSWER-A study performed where neither the treatment allocator nor the
participant nor the response gatherer knows which group the participant is in



Omission Error - ANSWER-An error because something ( for example, data or survey responses) is
missing.



Relational Database - ANSWER-A database structured to recognize relations among stored items of
information

, Ordinal Data - ANSWER-Data that places data objects into an order according o some quality with higher
order indicating more of that quality



Discrete Data - ANSWER-Data that can only take on whole values and has clear boundaries



Interval Data - ANSWER-Data that is ordered within a range and with each data point being an equal
interval apart



Valid Data - ANSWER-Data resulting from a test that accurately measures what it is intended to measure



Big Data - ANSWER-A catch-phrase that describes a massive volume that is so large that it's difficult to
process using traditional database software techniques



Systematic errors - ANSWER-Errors in measurement that are constant within a data set, sometimes
caused by faulty equipment or bias.



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



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



Statistics - ANSWER-The science that deals with the interpretation of numerical facts or data though
theories of probability. Also, the numerical facts or data themselves.



Decision Tree Analysis - ANSWER-The diagram of possible alternatives and their expected consequences
in order to formulate passible courses of action in order to make decisions



Expected Monetary Value (EMV) Analysis - ANSWER-A statistical technique that calculates the average
outcome when the future includes scenarios that may or may not happen.

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