Which of the following conditions should discourage the use of the one-toone
readings to combine data sets?
A) When a better method is available
B) All observations from each data set read should be contained in the
final data set
C) All variables from each data set read should be contained in the final
data set
D) Variables have the same name in multiple data sets
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SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries. ® indicates USA registration.
Other brand and product names are trademarks of their respective companies.
This blog is not responsible for any kind of copyright violation. This blog just collects the links hosted or posted by other servers/people/search engines.The creator of this page or the ISP(s) hosting any content on this site take no responsibility for the way you use the information provided on this site.If anybody has any copyright claim on it and doesn’t wish the information provided to be shown on our site, please do respond to this email. We shall remove them off immediately. Any inconvenience is regretted. Please do mention your exact grievance/problems with respect to certain third party links. We assure you that appropriate action will be taken off. Thank you
2 comments:
Answer: B
Reasoning: One-to-one readings are the simplest form of combining
data sets which will provide the best option in ensuring the
programming code is not overly complex. In this type of combining,
all the variables from each of the data sets will exist in the new data
set. Variables with the same name does not matter, since the values
of the last data set read will overwrite all previous values from existing
data sets. If the values should not be overwritten, the variable name
can be changed before the output is rendered. Not all observations
will appear in the final data set: if this is a requirement than
concatenation is the next best choice for combining data sets.
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