1.7 - Ethics & Responsible Analytics

Question 1

Why is ethics important in data analysis?

Answer 1

Ethical practices ensure that data is used responsibly, fairly, and does not harm individuals or groups.

Question 2

What does “responsible analytics” mean?

Answer 2

Using data and analysis in a way that is transparent, fair, respects privacy, and supports good decision-making.

Question 3

Name three key principles of responsible analytics.

Answer 3

Fairness, privacy, transparency

Question 4

Ensuring that data does not unfairly favor or disadvantage certain groups is an example of ______.

Answer 4

Fairness

Question 5

Protecting personal or sensitive information in datasets is an example of ______.

Answer 5

Privacy

Question 6

Making methods, assumptions, and results clear to others is an example of ______.

Answer 6

Transparency

Question 7

Which of these could be an ethical issue in data analysis?
A) Using biased survey questions
B) Sharing aggregated trends
C) Documenting assumptions
D) Cleaning duplicates

Answer 7

A) Using biased survey questions

Question 8

What is bias in data?

Answer 8

Bias occurs when data or analysis systematically favors certain outcomes or groups, leading to misleading or unfair conclusions.

Question 9

Give one way to reduce bias in data collection or analysis.

Answer 9

Examples: ensure diverse samples, validate data sources, use standardized measurements.

Question 10

Why is transparency important when sharing results?

Answer 10

It helps others understand how conclusions were reached and builds trust in the findings.

Question 11

Name one risk of ignoring ethical considerations in analytics.

Answer 11

Examples: discrimination, legal issues, loss of trust, harmful decisions.

Question 12

How can analysts balance privacy and usefulness of data?

Answer 12

By anonymizing sensitive information, aggregating data, and only collecting what’s necessary for analysis.