Question: To what does the phrase Garbage in , garbage out refer? Question 1 options: The need to keep a clean house Inventory management procedures The
To what does the phrase "Garbage in garbage out" refer?
Question options:
The need to keep a clean house
Inventory management procedures
The effect the quality of data has on decisions made informed by an analysis of those data
The effect that analyst ethics have on the quality of decisions
Question Mandatory points
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The value of a specific variable for a specific observation is
Question options:
a datum
data
univariate
categorical
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The response scale Spruce Hemlock Maple Oak Cedar will yield data.
Question options:
nominal
ordinal
interval
ratio
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The response scale Lowest Highest will yield data.
Question options:
nominal
ordinal
interval
ratio
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To calculate a percentage change between values, we need data.
Question options:
nominal
ordinal
interval
ratio
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Which data are not continuous or treated as continuous?
Question options:
US currency
Cargo shipping weights
Project completion times
Number of defects in production runs
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The closing values of the S&P Index for each trading day in are what type of data?
Question options:
Interval
Multivariate
Cross Sectional
Time Series
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Random sampling is used to minimizeeliminate
Question options:
bias
error
cost
effort
Question Mandatory points
Study a sample rather than a population when
Question options:
the population is small
the act of testingstudying destroys the item being testedstudied
the required sample size approaches the population size
there is a database containing the population data
Question Mandatory points
Selecting every kth item from an ongoing production line is
Question options:
simple random sampling
judgement sampling
systematic sampling
stratified sampling
Question Mandatory points
Response error can be caused by
Question options:
selection bias
social desirability
sampling error
lack of a true zero
Question Mandatory points
By using random sampling methods, the analyst demonstrates a bias toward
Question options:
random sampling error
expert judgement
convenience
bias
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