Standardizing data ensures uniformity and consistency across the dataset. A predefined mapping such as replacing "USA," "United States," and "U.S." with a single standardized value like "United States" avoids ambiguities during analysis. This method maintains data integrity and improves the dataset's usability for analytical tasks. Why Other Options Are Wrong : B) Removing inconsistent entries leads to data loss and reduced sample size. C) Choosing the most frequent entry ignores valid data variations and may bias results. D) Replacing entries with null values reduces the dataset's quality. E) Leaving the inconsistencies untreated causes challenges during data interpretation.
Read the given statements and conclusions carefully. Assuming that the information given in the statements is true, even if it appears to be at varianc...
Statements:
Some cost are amount.
At least some amount are interest.
100% interest are principle.
Only cost are compound.<...
Statements:Some pastries are cakes.
No cake is a pudding.
All puddings are sweets.
Conclusions:I. Some sweets are not cakes.
Statements: Apples # Banana Pears % Banana Papaya & Banana Grapes # Papaya
Conclusions:
I. Apples % Pears
II. Grapes ≤ Pa...
Statement:
Only a few Lion is Leopard.
All Leopard is Tiger.
Some Leopard is Onion.
Conclusion:
I. No Tiger ...
Statements:
Some guests are hosts
All hosts are invitations
No invitation is a decoration
Conclusion :
I. Some g...
Statement : Some letters are alphabets.
All alphabets are words.
Some ...
Statements: All wheat are rice.
Some rice are not pulses.
All pulses are oats.<...
Read the given statements and conclusions carefully. Assuming that the information given in the statements is true, even if it appears to be at varianc...
Statements:
All Pointers are Guns.
Only a few Guns are Cracker.
Some Cracker are not Bullets.
Conclusions:
<...