ETHICS IN DATA SCIENCE EXAM
QUESTIONS WITH VERIFIED
ANSWERS. A+ GRADE 2025/2026.
What are the limitations of the chosen approach? - ANS Built-in bias, e.g. voice recognition
not handling many accents, medical datasets skewed towards men
What is the recall regarding ethics in DS outputs? - ANS Conclusions and automated systems
can be used for good or ill, professionals have responsibility for uses made of their work
What is an example of unethical behavior in DS? - ANS Volkswagen detecting air-quality tests
and switching to lower-polluting mechanisms only during the test
What is the importance of professional ethics? - ANS Defines expected behavior, required for
membership in professional associations
Who are the stakeholders in data science? - ANS Clients/employers, subjects described by
data, workers whose jobs might be displaced, end-users whose environment might be shaped
What are the principles of computing professional ethics? - ANS Contribute to society, avoid
harm, be fair, respect privacy, respect others' work, work within competence, prioritize public
good
1 @COPYRIGHT 2025/2026 ALLRIGHTS RESERVED
, What is data quality? - ANS Data quality is essential for useful results.
What does 'garbage in, garbage out' mean? - ANS 'Garbage in, garbage out' means that if the
input data is of poor quality, the output results will also be of poor quality.
Why is it important to have good data sources? - ANS Good data sources ensure that the
whole provenance chain is trusted and that the data is representative of the actual domain.
What is the process of cleaning data? - ANS Cleaning data involves improving data quality as
much as possible for specific uses.
Why is it easier to automate analysis in Python than in Excel? - ANS Python allows for easier
automation and testing compared to Excel, which often contains unnoticed errors in formulas
and data.
Why is it important to know the limitations of the techniques used in data analysis? -
ANS Knowing the limitations helps in checking the applicability of the techniques and
ensures accurate results.
What is the significance of scatterplots in data analysis? - ANS Scatterplots with all the data
are helpful in spotting overall trends and patterns between attributes.
Why should one be skeptical and ready to step away from initial findings in data analysis? -
ANS Being skeptical helps in avoiding biased or incorrect conclusions and promotes objective
analysis.
Why is it important to be open about limitations when communicating results? - ANS Being
transparent about limitations prevents overclaiming and ensures accurate interpretation of the
results.
2 @COPYRIGHT 2025/2026 ALLRIGHTS RESERVED
QUESTIONS WITH VERIFIED
ANSWERS. A+ GRADE 2025/2026.
What are the limitations of the chosen approach? - ANS Built-in bias, e.g. voice recognition
not handling many accents, medical datasets skewed towards men
What is the recall regarding ethics in DS outputs? - ANS Conclusions and automated systems
can be used for good or ill, professionals have responsibility for uses made of their work
What is an example of unethical behavior in DS? - ANS Volkswagen detecting air-quality tests
and switching to lower-polluting mechanisms only during the test
What is the importance of professional ethics? - ANS Defines expected behavior, required for
membership in professional associations
Who are the stakeholders in data science? - ANS Clients/employers, subjects described by
data, workers whose jobs might be displaced, end-users whose environment might be shaped
What are the principles of computing professional ethics? - ANS Contribute to society, avoid
harm, be fair, respect privacy, respect others' work, work within competence, prioritize public
good
1 @COPYRIGHT 2025/2026 ALLRIGHTS RESERVED
, What is data quality? - ANS Data quality is essential for useful results.
What does 'garbage in, garbage out' mean? - ANS 'Garbage in, garbage out' means that if the
input data is of poor quality, the output results will also be of poor quality.
Why is it important to have good data sources? - ANS Good data sources ensure that the
whole provenance chain is trusted and that the data is representative of the actual domain.
What is the process of cleaning data? - ANS Cleaning data involves improving data quality as
much as possible for specific uses.
Why is it easier to automate analysis in Python than in Excel? - ANS Python allows for easier
automation and testing compared to Excel, which often contains unnoticed errors in formulas
and data.
Why is it important to know the limitations of the techniques used in data analysis? -
ANS Knowing the limitations helps in checking the applicability of the techniques and
ensures accurate results.
What is the significance of scatterplots in data analysis? - ANS Scatterplots with all the data
are helpful in spotting overall trends and patterns between attributes.
Why should one be skeptical and ready to step away from initial findings in data analysis? -
ANS Being skeptical helps in avoiding biased or incorrect conclusions and promotes objective
analysis.
Why is it important to be open about limitations when communicating results? - ANS Being
transparent about limitations prevents overclaiming and ensures accurate interpretation of the
results.
2 @COPYRIGHT 2025/2026 ALLRIGHTS RESERVED
