This quiz focuses on SAS data management techniques, specifically on combining and merging datasets. It assesses skills in creating new datasets from existing ones, handling variables during merging, and understanding the outcomes of various data manipulation methods in SAS.
Data actors.props3; set actors.props1; set actors.props2; run;
Data actors.props3; set actors.props1 actors.props2; run;
Data actors.props3; set actors.props1 actors.props2; by actor run;
Data actors.props3; merge actors.props1 actors.props2; by actor run;
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None of the above
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Missing
$30,000
$40,000
You cannot concatenate these data sets.
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The values of Age in the 1st data set overwrite the values of Age in the 2nd data set.
The values of Age in the 2nd data set overwrite the values of Age in the 1st data set.
The DATA step fails to because the two data sets contain same-named variables that have different values.
The values of Age in the 2nd data set are set to missing.
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None of the above
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Data ensemble.merged; merge ensemble.spring(in=blue) ensemble.summer; by fabric; run;
Data ensemble.merged; merge ensemble.spring(out=blue) ensemble.summer; by fabric; run;
Data ensemble.merged; merge ensemble.spring(blue=navy) ensemble.summer; by fabric; run;
Data ensemble.merged; merge ensemble.spring(rename=(blue=navy)) ensemble.summer; by fabric; run;
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The Merged data set contains some missing values because not all observations have matching observations in the other data set.
The Merged data set contains eight observations
The DATA step produces errors.
Values for Units in Blood.Donors2 overwrite values of Units in Blood.Donors1.
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4
5
6
9
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$4,000
$3,000
Missing
Can't tell from the information given
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