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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