WGU C207 (Data-Driven Decision Making) EXAM
COMPLETE QUESTIONS WITH DETAILED VERIFIED
ANSWERS /ALREADY GRADED A+
When do we do the analytics in the decision-making process? Before, after, during, or in-
between?
Before
When do we measure in the decision-making process? Before, after, during, or in-between?
After
Why do we use data to make decision?
To make a fact based decision and accurate predications.
Data Management seeks to provide data that is what?
Relevant, Complete, Accurate, Available, Timely
The three types of analytics
Descriptive, Predictive, Prescriptive
Descriptive Analytics
Discussing current and past information. No predictions about the future
Predictive Analytics
Using the past to predict the future
Prescriptive Analytics
Using the past to predict the future AND optimize the situation.
Sorting out your spreadsheet can help find what?
Out of range and Omission
,What is a random error?
If the error will fix itself, is unknown and unpredictable, and can be minimized by a larger
sample size
What is a systematic error?
If the error will NOT fix itself. You must fix it. Is a constant measurement error, and can be
caused by measurement instruments or experimental design
Skewness
A measure of the degree to which a probability distribution "leans" toward one side of the
average, where the median and mean are not the same
Relational Database
A database structured to recognize relations among stored items of information
Outlier
Observation points that are distant from others
Reliable Data
Consistent and repeatable
Valid Data
Measures what is intended to be measured
Measurement Bias
A prejudice in the data that results in inaccurate measure. This can result from faulty
measurement tools, misclassification of the sample, or failing to correctly measure the right
variable.
Selection Bias
, A bias introduced within the sample of the study. Sample Size must be - Representative,
Random, Large Enough (at least 30 samples)
Information (Response) Bias
Respondent says what they believe the questioner wants to hear or Surveyor is actively seeking
a certain response
Big Data
Both Structured and Unstructured data in such large volumes that it's difficult to process using
traditional database and software techniques
Data Mining
The process of searching through customer data in order to detect patterns to guide marketing
decision making, but will overlook underlying causes
Theme Analysis
Used on unstructured data to identify common words amongst responses
Continuous Data
A data point that can lay along any point in a range of data. An example might be age. It is
possible to be 22.67 years old
Discrete Data
Can only take on whole values and has clear boundaries. It is not possible to own 3.4 cars; you
either own three cars or four
Nominal
No Number, No sequence (Think - colors of cars). Discrete Data. Sometimes called "Categorical
Data". Think "NO Order".
Ordinal
COMPLETE QUESTIONS WITH DETAILED VERIFIED
ANSWERS /ALREADY GRADED A+
When do we do the analytics in the decision-making process? Before, after, during, or in-
between?
Before
When do we measure in the decision-making process? Before, after, during, or in-between?
After
Why do we use data to make decision?
To make a fact based decision and accurate predications.
Data Management seeks to provide data that is what?
Relevant, Complete, Accurate, Available, Timely
The three types of analytics
Descriptive, Predictive, Prescriptive
Descriptive Analytics
Discussing current and past information. No predictions about the future
Predictive Analytics
Using the past to predict the future
Prescriptive Analytics
Using the past to predict the future AND optimize the situation.
Sorting out your spreadsheet can help find what?
Out of range and Omission
,What is a random error?
If the error will fix itself, is unknown and unpredictable, and can be minimized by a larger
sample size
What is a systematic error?
If the error will NOT fix itself. You must fix it. Is a constant measurement error, and can be
caused by measurement instruments or experimental design
Skewness
A measure of the degree to which a probability distribution "leans" toward one side of the
average, where the median and mean are not the same
Relational Database
A database structured to recognize relations among stored items of information
Outlier
Observation points that are distant from others
Reliable Data
Consistent and repeatable
Valid Data
Measures what is intended to be measured
Measurement Bias
A prejudice in the data that results in inaccurate measure. This can result from faulty
measurement tools, misclassification of the sample, or failing to correctly measure the right
variable.
Selection Bias
, A bias introduced within the sample of the study. Sample Size must be - Representative,
Random, Large Enough (at least 30 samples)
Information (Response) Bias
Respondent says what they believe the questioner wants to hear or Surveyor is actively seeking
a certain response
Big Data
Both Structured and Unstructured data in such large volumes that it's difficult to process using
traditional database and software techniques
Data Mining
The process of searching through customer data in order to detect patterns to guide marketing
decision making, but will overlook underlying causes
Theme Analysis
Used on unstructured data to identify common words amongst responses
Continuous Data
A data point that can lay along any point in a range of data. An example might be age. It is
possible to be 22.67 years old
Discrete Data
Can only take on whole values and has clear boundaries. It is not possible to own 3.4 cars; you
either own three cars or four
Nominal
No Number, No sequence (Think - colors of cars). Discrete Data. Sometimes called "Categorical
Data". Think "NO Order".
Ordinal
