Module One Summative Quiz:The Data Scientist’s Toolbox(Data Science Specialization):Answers2025

Question 1

Which of these is NOT one of the main skills embodied by data scientists?

• ❌ Hacking skills

• ❌ Math and stats

• ✅ Machine learning

Explanation:
The three core skills of a data scientist are often represented by the “Data Science Venn Diagram” —
1️⃣ Hacking skills (practical coding)
2️⃣ Math & statistics knowledge
3️⃣ Substantive expertise (domain knowledge)
Machine learning is a tool or subset of data science, not one of the three foundational skill areas.

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Question 2

What is the most important thing in Data Science?

• ✅ The question you are trying to answer

• ❌ Statistical inference

• ❌ Working with large data sets

Explanation:
Data science begins with asking the right question. Without a clear, well-defined question, no amount of data or modeling can provide meaningful insights.

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Question 3

Which of these might be a good title for a forum post?

• ❌ URGENT! R isn’t working!

• ✅ Removing rows with NAs in data.frame using subset(), R 3.4.3

• ❌ How do I get rnorm() to work?

Explanation:
A good post title is clear, descriptive, and specific — it tells readers exactly what the issue is and helps others find it later. “URGENT” or vague titles are discouraged.

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Question 4

What’s the first step in the data science process?

• ❌ Communicate your findings

• ❌ Exploring the data

• ✅ Generating the question

Explanation:
Before you explore or analyze, you must first formulate a meaningful, data-driven question. This guides the rest of the data science workflow — data collection, analysis, and communication.

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Question 5

Which of these is an example of a quantitative variable?

• ✅ Latitude

• ❌ Occupation

• ❌ Educational level

Explanation:
Quantitative variables are numeric and can be measured or ordered mathematically. Latitude is a continuous numeric variable. Occupation and education level are categorical (qualitative).

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🧾 Summary Table

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