Practice Data Validation And Cleaning (19.6) - INPUT - CBSE 9 AI (Artificial Intelligence)

Practise this section

9 questions

Flashcard drill
3 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
Sign up to start the exercise
Quiz
3 questions · about 2 min · pass mark 70%. Hints available.
Sign up to start the quiz

6 sample questions

Question 1.
What is imputation?
Show hintHide hint
Think about how you would replace blank spots in data.
Question 2.
List two common problems associated with data.
Show hintHide hint
Recall the issues we discussed with data quality.
3Question 3.
What is the effect of missing values on a dataset?
- They improve accuracy
- They can lead to bias
- They have no impact
Show hintHide hint
Consider how missing information can affect conclusions.
4Question 4.
Can normalization change how a dataset is interpreted?
- True
- False
Show hintHide hint
Think about how adjustments in numbers might change your understanding.
Question 5.
You are given a dataset with 500 entries, and 100 of them have missing values. Describe how you would approach cleaning this dataset.
Show hintHide hint
Think about how significant those missing entries are to your analysis.
Question 6.
If a data analysis revealed that outliers were consistently skewing the results, what steps would you take to identify and deal with them?
Show hintHide hint
Consider the implications of outliers on your analysis results.

5 more questions in this section. Enroll free to practise them all.