MCQs

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Overall MCQs for Reference

What is data accuracy in data science?
a. The closeness of data to its true value
b. The ability to repeat measurements
c. The speed of data processing
d. The total amount of data collected
Answer: a. The closeness of data to its true valuestudysmarter+1
Which principle ensures that data correctly reflects real-world values?
a. Data anonymization
b. Data profiling
c. Data accuracy
d. Data encryption
Answer: c. Data accuracycollibra+1
What is the primary purpose of data validation?
a. To analyze data performance
b. To ensure data accuracy by preventing errors
c. To enrich dataset with more features
d. To increase data storage
Answer: b. To ensure data accuracy by preventing errorsmontecarlodata+1
How is ‘accuracy’ commonly measured in datasets?
a. By summing all values
b. By comparing data against known standards
c. By counting missing values
d. By evaluating model speed
Answer: b. By comparing data against known standardsatlan+1
Which metric evaluates how close a measured value is to its actual value?
a. Precision
b. Recall
c. Accuracy
d. F1-score
Answer: c. Accuracymontecarlodata+1
What step helps maintain data accuracy in large organizations?
a. Automated data entry
b. Manual error reports
c. Random removal of data
d. Ignoring duplicates
Answer: a. Automated data entryibm+1
Which technique is used to spot inconsistencies in datasets?
a. Data profiling
b. Data archiving
c. Data decentralization
d. Data compression
Answer: a. Data profilingatlan+1
Which factor poses a challenge to data accuracy?
a. Low data volume
b. Complex data integration
c. Simple data structure
d. Reduced reporting
Answer: b. Complex data integrationstudysmarter+1
The term “trueness” in reference to data accuracy means:
a. Repeatability among measurements
b. Closeness to reference value
c. Amount of data captured
d. Format of the data
Answer: b. Closeness to reference valuetestbook
What is the result of poor data accuracy in business analytics?
a. Faster data processing
b. Inaccurate insights
c. Reduced data redundancy
d. Increased security
Answer: b. Inaccurate insightsskillfloor+1
A common method for improving data accuracy in cloud-based systems is:
a. Ignoring real-time updates
b. Implementing real-time data validation
c. Isolating datasets permanently
d. Disabling feedback loops
Answer: b. Implementing real-time data validationstudysmarter
Which of the following is NOT a component of data quality control?
a. Validity checks
b. Random deletion
c. Standardization
d. Accurate data capture
Answer: b. Random deletionacceldata
What does data validation usually check for?
a. Incomplete columns only
b. Duplicates only
c. Invalid entries, missing values, duplicates
d. File formats
Answer: c. Invalid entries, missing values, duplicatesdataexpertise+1
Data which is consistent across multiple datasets is considered:
a. Faulty
b. Redundant
c. Accurate
d. Anomalous
Answer: c. Accurateacceldata+1
What does a “feedback loop” help achieve in data accuracy?
a. Real-time correction of errors
b. Data storage expansion
c. Data encryption
d. Release of new features
Answer: a. Real-time correction of errorsatlan
Accuracy can be improved by:
a. Increasing processing speed
b. Implementing validation rules
c. Data isolation
d. Deleting old data
Answer: b. Implementing validation rulesibm+1
What is a key benefit of standardizing data formats?
a. Higher data redundancy
b. Consistency and improved accuracy
c. Less secure data
d. Random data allocation
Answer: b. Consistency and improved accuracyacceldata+1
When data is duplicated in a dataset, accuracy:
a. Improves
b. Is unaffected
c. Decreases
d. Transforms
Answer: c. Decreasesdataexpertise+1
In data science, ‘spot checks’ are used for:
a. Increasing recall
b. Measuring accuracy via sample testing
c. Deleting old records
d. Encrypting sensitive data
Answer: b. Measuring accuracy via sample testingatlan
What is required for ‘high accuracy’ in measurement instruments?
a. High resolution
b. High sensitivity
c. High linearity
d. High conformity to true value
Answer: d. High conformity to true valuetestbook
Data quality control includes assessing which aspect?
a. Mean value only
b. Completeness and relevance
c. Speed of data processing
d. Volume of data
Answer: b. Completeness and relevanceacceldata
Automated validation processes in data accuracy serve to:
a. Guarantee encryption
b. Prevent large-scale errors
c. Secure backups
d. Improve clustering
Answer: b. Prevent large-scale errorsmontecarlodata+1
The formula commonly used for sales accuracy is:
a. (Total Sales)/(Correctly Recorded Sales) × 100%
b. (Correctly Recorded Sales)/(Total Sales) × 100%
c. (Total Sales) – (Correctly Recorded Sales) × 100%
d. (Correctly Recorded Sales) × 100%
Answer: b. (Correctly Recorded Sales)/(Total Sales) × 100%studysmarter
What does “error rate calculation” involve?
a. Comparing predicted versus actual data
b. Encrypting data
c. Generating synthetic data
d. Ignoring missing data
Answer: a. Comparing predicted versus actual dataatlan
Which is necessary for compliance in regulated industries regarding data?
a. Accurate, consistent, and validated data
b. Frequent data deletion
c. Data anonymization only
d. Data compression
Answer: a. Accurate, consistent, and validated datacollibra+1
Historical trend analysis helps in:
a. Identifying consistent accuracy over time
b. Compressing files
c. Encrypting all columns
d. Data duplication
Answer: a. Identifying consistent accuracy over timeatlan
Inaccuracy in data can stem from:
a. Erroneous data entry
b. Regular audits
c. High resolution
d. Standard coding schemes
Answer: a. Erroneous data entrymontecarlodata+1
The “ratio of relevant data to retrieved data” is:
a. Accuracy
b. Precision
c. Recall
d. Mean
Answer: b. Precisionmontecarlodata
Accuracy is most affected during:
a. Data transformation
b. Data visualization
c. Data annotation
d. Data encryption
Answer: a. Data transformationacceldata+1
What is a KPI commonly used for assessing data accuracy?
a. Error rate
b. Server uptime
c. Encryption key length
d. Data storage volume
Answer: a. Error rateatlan
Standardization in data science refers to:
a. Consistent formatting and coding
b. Increasing data redundancy
c. Isolating datasets
d. Regular encryption
Answer: a. Consistent formatting and codingstudysmarter+1
The “F1-score” in data analysis combines:
a. Mean and standard deviation
b. Precision and recall
c. Sensitivity and error rate
d. Volume and speed
Answer: b. Precision and recallmontecarlodata
In data science, what does completeness refer to?
a. Having all relevant information for its purpose
b. Encrypting everything
c. Random data sampling
d. Ignoring outliers
Answer: a. Having all relevant information for its purposestudysmarter+1
Data accuracy is essential for:
a. Reliable decision-making
b. Minimizing data storage
c. Rapid visualization
d. Algorithm comparison
Answer: a. Reliable decision-makingibm+1
Which is NOT a best practice for data accuracy?
a. Regular data audits
b. Cross-referencing with trusted sources
c. Ignoring validation results
d. Automated data entry
Answer: c. Ignoring validation resultsdataexpertise+1
Data quality problems typically increase:
a. Reliability
b. Inaccurate insights
c. Security
d. Visualization options
Answer: b. Inaccurate insightsskillfloor+1
Which tool is used to assess and improve data accuracy?
a. Data auditing tool
b. Data visualization library
c. Data anonymization algorithm
d. Feature extraction suite
Answer: a. Data auditing tooldataexpertise+1
A feedback loop in data accuracy refers to:
a. Continuous error correction process
b. Repeating data backup
c. Multiple copies of datasets
d. Encrypting feedback messages
Answer: a. Continuous error correction processatlan
How can organizations avoid overloading in data accuracy processes?
a. Implement error reports
b. Restrict dataset size
c. Ignore accuracy metrics
d. Avoid regular audits
Answer: a. Implement error reportsoutsource2india
What role does consistency play in data accuracy?
a. Ensures duplicate entries
b. Guarantees secure backups
c. Ensures uniform values and formats
d. Encrypts the data
Answer: c. Ensures uniform values and formatsacceldata+1
Regular reviews of business data help to:
a. Maintain accuracy
b. Increase storage
c. Ensure duplication
d. Motivate encryption
Answer: a. Maintain accuracyoutsource2india+1
What is a challenge with dynamic data regarding accuracy?
a. Needs up-to-date monitoring
b. Requires less validation
c. Increases recall
d. Needs more encryption
Answer: a. Needs up-to-date monitoringstudysmarter+1
What is implied by timely data accuracy?
a. Data is up-to-date
b. Data is compressed
c. Data has fewer columns
d. Encryption is implemented
Answer: a. Data is up-to-dateacceldata+1
Cross-referencing data entries with historical datasets ensures:
a. Data consistency
b. Data loss
c. Data redundancy
d. Data obsolescence
Answer: a. Data consistencystudysmarter+1
Data enrichment improves accuracy by:
a. Adding valuable context to data
b. Increasing data redundancy
c. Slowing processing speed
d. Removing useful features
Answer: a. Adding valuable context to datadataexpertise
Which dimension of data quality is most linked to accuracy?
a. Precision
b. Consistency
c. Timeliness
d. Accuracy itself
Answer: d. Accuracy itselfibm+1
Which process involves “real-world cross-checks” for accuracy?
a. Data migration
b. Data validation
c. Data aggregation
d. Data encryption
Answer: b. Data validationsailpoint+1
Data quality problems may lead to:
a. Misleading decision-making
b. Higher accuracy
c. Lower redundancy
d. Faster reporting
Answer: a. Misleading decision-makingskillfloor+1
One way to minimize human error in collecting data is:
a. Automating data entry
b. Increasing manual audits
c. Ignoring validation checks
d. Removing constraints
Answer: a. Automating data entryibm+1
When merging datasets for analysis, accuracy problems can arise due to:
a. Integration and transformation errors
b. Increased encryption
c. Data redundancy
d. Regular validation checks
Answer: a. Integration and transformation errorsmontecarlodata+1

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