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Module 4 challenge :Foundations: Data, Data, Everywhere (Google Data Analytics Professional Certificate) Answers 2025

Question 1

Which of the following statements accurately describe fairness considerations in data analysis?

✅ Best practices for fairness in data analysis include considering context.
✅ Fairness means ensuring that analysis does not create or reinforce bias.
✅ A data professional may choose to use oversampling when prioritizing fairness.
❌ Fairness practices should begin during the process phase of the data analysis process.

Explanation:
Fairness starts at the beginning of the project — not only during processing. Considering context, avoiding bias, and using oversampling help ensure equitable analysis.


Question 2

An HR firm targets job ads only to women based on data. What should they have done instead?

✅ Conduct more research to understand the surrounding factors of this situation.
❌ Only target the ads for men.
❌ Ask executives who to target.
❌ Find data that supports targeting women.

Explanation:
Fairness requires understanding context — not making assumptions from incomplete data. The team should have explored why most admin assistants are women before deciding.


Question 3

Which fairness best practice helps teams understand the context of data conclusions?

✅ Identify surrounding factors
❌ Include self-reported data
❌ Use oversampling
❌ Consider relevant data

Explanation:
“Identifying surrounding factors” means considering social, historical, or cultural contexts that influence data — ensuring fair interpretation.


Question 4

Peak ridership occurs between 7 AM and 7 PM. Fairness could be improved by over-sampling which group?

✅ Passengers who ride the train during off-peak times
❌ Passengers who ride during peak times
❌ Senior citizens
❌ Young professionals

Explanation:
To get a balanced sample, you oversample underrepresented groups — in this case, off-peak riders.


Question 5

Fill in the blank: A junior data analyst works on a _____ when using their analytical skills to address questions or problems for their organization.

✅ business task
❌ measurable outcome
❌ stated objective
❌ relevant process

Explanation:
A business task is the specific question or problem an analyst addresses using data insights.


Question 6

A grocery store data professional uses customer surveys instead of employee observations to reduce bias. Which fairness best practice is this?

✅ Self-reporting
❌ Oversampling
❌ Considering context
❌ Using all available data

Explanation:
Collecting self-reported data minimizes third-party bias and provides direct, fairer insights from participants themselves.


Question 7

A hospital analyst includes demographics, medical history, and lifestyle to study blood pressure. Which fairness best practice is this?

✅ Considering all available data
❌ Oversampling
❌ Including self-reported data
❌ Guiding business strategy

Explanation:
Using all available data prevents narrow or biased analysis by incorporating multiple relevant factors.


Question 8

Fill in the blank: A data professional considers fairness from the start to when their organization _____ to ensure their analysis is fair.

✅ acts on the data insights
❌ cleans and organizes the data
❌ collects data for the project
❌ presents findings to stakeholders

Explanation:
Fairness must be maintained throughout the process — especially when the organization acts on insights, as actions directly affect people.


🧾 Summary Table

Q# ✅ Correct Answer(s) Key Concept
1 1, 2, 4 ✅ Fairness principles & practices
2 Conduct more research ✅ Understanding data context
3 Identify surrounding factors ✅ Context awareness
4 Off-peak riders ✅ Oversampling fairness
5 business task ✅ Analyst’s core responsibility
6 Self-reporting ✅ Reducing bias
7 Considering all available data ✅ Comprehensive, fair analysis
8 acts on the data insights ✅ Maintaining fairness end-to-end