Module 1: Introducing Data Analytics and Analytical Thinking Answers (Part 2: Q16–30)
This is Part 2 of the Module 1 quiz answers for “Introducing Data Analytics and Analytical Thinking” from the Google Data Analytics Professional Certificate on Coursera.
Here, we’ll walk through questions 16 to 30 with detailed explanations to support your learning.
To find answers to the remaining questions, check out the full module breakdown below:
16. In order to create clear and engaging discussions in the forum, which type of writing styles should you use? Select all that apply.
- Including proper punctuation, such as commas and periods ✅
- Writing in complete sentences ✅
- Writing in text message language, such as BTW for “by the way”
- Typing in all lowercase
Explanation:
Using professional language, proper grammar, and punctuation is crucial for effective communication in discussion forums. Writing clearly ensures that your message is understood and engages other learners in meaningful conversations. Avoid informal writing styles such as text message language or typing in all lowercase.
17. When posting in the discussion forum, what type of behavior is acceptable?
- Using cursing to emphasize your point
- Being sensitive, kind, and open-minded ✅
- Conveying your opinion clearly by arguing against someone’s perspective
- Sharing advertisements and product promotions
Explanation:
Creating a respectful and inclusive environment is vital for productive discussions. Being considerate of others’ perspectives and maintaining a positive tone fosters collaboration and enhances the learning experience. Avoid using offensive language or promoting personal products.
*Module 1 challenge*
Graded Quiz
18. Data analysis is the various elements that interact with one another in order to provide, manage, store, organize, analyze, and share data.
- True
- False ✅
Explanation:
That’s a description of a data ecosystem, not data analysis, which is about examining data to draw conclusions.
19. In data analytics, a model is a group of elements that interact with one another.
- True
- False ✅
Explanation:
That describes a system or ecosystem, not a model, which is a simplified representation of reality used for analysis.
20. Fill in the blank: The primary goal of a data _____ is to create new questions using data.
- designer
- analyst
- engineer
- scientist ✅
Explanation:
Data scientists often form hypotheses and generate questions to explore new insights from data.
21. Fill in the blank: The term _____ is defined as an intuitive understanding of something with little or no explanation.
- personal opinion
- rational thought
- gut instinct ✅
- awareness
Explanation:
Gut instinct involves intuition, not data or logical reasoning.
22. A company defines a problem it wants to solve. Then, a data analyst gathers relevant data, analyzes it, and uses it to draw conclusions. The analyst shares their analysis with subject-matter experts, who validate the findings. Finally, a plan is put into action. What does this scenario describe?
- Data science
- Data-driven decision-making ✅
- Customer service
- Identification of trends
Explanation:
This is the classic process of using data to inform decisions and verify them with experts.
23. What do subject-matter experts do to support data-driven decision-making? Select all that apply.
- Offer insights into the business problem ✅
- Review the results of data analysis and identify any inconsistencies ✅
- Collect, transform, and organize data
- Validate the choices made as a result of the data insights ✅
Explanation:
SMEs interpret results in context, spot errors, and ensure that data insights make practical sense.
24. You have just finished analyzing data for a marketing project. Before moving forward, you share your results with members of the marketing team to see if they might have additional insights into the business problem. What practice does this support?
- Data analytics
- Data science
- Data-driven decision-making ✅
- Data management
Explanation:
Getting feedback before final decisions ensures collaboration and improved accuracy.
25. You read an interesting article about data analytics in a magazine and want to share some ideas from the article in the discussion forum. In your post, you include the author and a link to the original article. This would be an inappropriate use of the forum.
- True
- False ✅
Explanation:
Sharing relevant resources with attribution is encouraged in discussion forums.
26. Which of the following options describes data analysis?
- The various elements that interact with one another in order to provide, manage, store, organize, analyze, and share data
- Creating new ways of modeling and understanding the unknown by using raw data
- The collection, transformation, and organization of data in order to draw conclusions, make predictions, and drive informed decision-making ✅
- Using facts to guide business strategy
Explanation:
That’s the correct definition—data analysis is about turning raw data into insight.
27. In data analytics, what term describes a collection of elements that interact with one another to produce, manage, store, organize, analyze, and share data?
- The cloud environment
- A modeling system
- A data ecosystem ✅
- A database
Explanation:
A data ecosystem includes all tools, storage, people, and processes interacting with data.
28. Select the best description of gut instinct.
- Choosing facts that complement your personal experiences
- An intuitive understanding of something with little or no explanation ✅
- Manipulating data to match your intuition
- Using your innate ability to analyze results
Explanation:
Gut instinct is subjective and often lacks data backing.
29. A furniture manufacturer wants to find a more environmentally friendly way to make its products. A data analyst helps solve this problem by gathering relevant data, analyzing it, and using it to draw conclusions. The analyst then shares their analysis with subject-matter experts from the manufacturing team, who validate the findings. Finally, a plan is put into action. This scenario describes data-driven decision making.
- True ✅
- False
Explanation:
This matches the exact steps in data-driven processes.
30. Fill in the blank: _______ are an important part of data-driven decision-making because they are people familiar with the business problem and can offer insight into the results of data analysis.
- Customers
- Competitors
- Subject-matter experts ✅
- Stakeholders
Explanation:
SMEs bring domain-specific knowledge and help interpret analysis outcomes correctly.
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