Learn why data accuracy and consistency are crucial for reliable data analysis, as demonstrated through a case of handling variations in survey responses.
Table of Contents
Question
A data analyst is reviewing the results of a survey. Respondents used the terms “avg,” “average,” and “avg.” throughout the survey in a response for the word “average.” Because of this, the analyst changed all related answers to say “average.” Which of the following are reasons why the analyst MOST likely made these changes? (Choose two.)
A. Data attribute limitations
B. Data accuracy
C. Data completeness
D. Data manipulation
E. Data blending
F. Data consistency
Answer
B. Data accuracy
F. Data consistency
Explanation
The analyst’s actions directly address data accuracy by ensuring all responses reflect the intended meaning, eliminating variations in expression. This also promotes data consistency, creating uniformity and avoiding misinterpretations during analysis due to inconsistent terminology.
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