Practice Data Cleaning And Preparation (12.3.3)

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9 questions

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6 sample questions

Question 1.
What is data cleaning?
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It involves making sure the data is accurate.
Question 2.
Why are missing values a problem in data analysis?
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Think about what happens if we base decisions on incomplete information.
3Question 3.
What is data cleaning?
- Removing duplicates
- Making data accurate
- Both of the above
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Think about all the things you would do to ensure data’s reliability.
4Question 4.
True or False: Normalization ensures all entries in a dataset are in the same format.
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Consider how this would affect comparing different data points.
Question 5.
Given a dataset with mixed formats for dates (e.g., MM/DD/YYYY and DD/MM/YYYY), what steps would you take to ensure all date entries are uniform?
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Think about how you would set a standard for all data points.
Question 6.
A dataset with 20% missing values across key fields is provided. Discuss the pros and cons of imputation vs. deletion for handling these values.
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Consider what you gain and lose with each approach.

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