Module 5: Endless Career Possibilities Answers (Part 3: Q31–45)
This is Part 3 of the Module 5 quiz answers for “Endless Career Possibilities)” from the Google Data Analytics Professional Certificate on Coursera.
Here, we’ll walk through questions 31 to 45 with detailed explanations to support your learning.
To find answers to the remaining questions, check out the full module breakdown below:
31. Fill in the blank: In data analytics, a topic to investigate is also known as a(n) _____.
- theme
- issue ✅
- question
- statement
Explanation:
An issue is a broad subject area that might contain multiple questions or problems needing investigation.
32. When a choice is made between good, bad, or a combination of consequences based on facts, it is also known as what?
- Data-driven decision-making ✅
- Data ethics
- Data visualization
- Data programming
Explanation:
This involves analyzing data to make informed and strategic business decisions.
33. At what point in the data analysis process should a data analyst consider fairness?
- When decisions are made based on the conclusions
- When data collection begins ✅
- When data is being organized for reporting
- When conclusions are presented
Explanation:
Bias can be introduced early, so fairness must be prioritized from the start of data collection.
34. A restaurant is considering changing their operating hours. They survey customers that come in between 4 p.m. and 5 p.m. to get feedback on this potential change. What can the restaurant do to ensure the data analysis process is fair?
- Expand the times when they survey customers ✅
- Survey only repeat customers
- Reward customers for participating in the survey
- Survey people walking by on the street
Explanation:
Surveying at different times avoids sampling only one group and gives a fuller picture.
35. A doctor’s office discovers that patients are waiting 20 minutes longer for their appointments than in past years. In what ways could a data analyst help solve this problem? Select all that apply.
- Analyze the average length of an appointment this year compared to past years. ✅
- Analyze the number of patients seen per day compared to past years. ✅
- Analyze a recent change in the average rating for the doctor’s office on social media.
- Analyze how many doctors and nurses are on staff at a given time compared to the number of patients with appointments ✅
Explanation:
These actions directly address factors that influence wait times, such as patient volume, appointment duration, and staffing levels. Social media ratings are unrelated to this operational issue.
36. Fill in the blank: Fairness is achieved when data analysis doesn’t create or _____ bias.
- reinforce ✅
- constrain
- highlight
- resolve
Explanation:
Bias is harmful when it’s perpetuated by flawed or incomplete data analysis.
37. A gym wants to start offering exercise classes. A data analyst plans to survey 10 people to determine which classes would be most popular. To ensure the data collected is fair, what steps should they take? Select all that apply.
- Ensure participants represent a variety of profiles and backgrounds. ✅
- Collect data anonymously. ✅
- Survey only people who don’t currently go to the gym.
- Increase the number of participants. ✅
Explanation:
These steps improve diversity, confidentiality, and reliability of the results.
38. A doctor’s office has discovered that patients are waiting 20 minutes longer for their appointments than in past years. A data analyst could help solve this problem by analyzing how many doctors and nurses are on staff at a given time compared to the number of patients with appointments.
- True ✅
- False
Explanation:
Staff-to-patient ratios are directly linked to appointment delays and can guide improvements.
39. Fill in the blank: Once an analyst has identified a problem for a business, they establish a(n)_____ to help inform the process of gathering the correct information.
- issue
- business task ✅
- statement
- solution
Explanation:
A business task helps clarify what data is needed and how to use it effectively.
40. Which of the following best describes what fairness in data analytics means?
- Ensuring that analysis does not create or reinforce bias ✅
- Including data from dominant groups
- Collecting data objectively
- Including self-reported data
Explanation:
Fairness is about making sure the analysis is inclusive, balanced, and unbiased.
41. A college IT department needs to reduce the number of computers on campus for student use. How could a data analyst help identify a solution to this problem?
- Analyze the number of classes schedules across all classrooms
- Analyze the utilization of the computer labs on campus ✅
- Analyze data on the number of students enrolled
- Analyze the square footage of all computer labs on campus
Explanation:
Understanding how often and how many students actually use the computer labs helps determine which computers are essential. This data-driven insight helps in making efficient reduction decisions.
42. Data analysts answer questions and solve problems. These are called business tasks.
- True ✅
- False
Explanation:
Business tasks involve solving problems and answering questions that are crucial for achieving organizational goals.
43. While working on an analysis, a data analyst learns that their team did not account for bias when they originally gathered the data. How might this factor affect the conclusion produced by the analysis?
- The analysis could result in a low sample size.
- The analysis could create a modeling error.
- The analysis could lead to a lack of anonymity.
- The analysis could present an incomplete picture. ✅
Explanation:
Ignoring bias can skew results, leading to conclusions that don’t reflect reality or exclude critical groups or variables.
44. In data analytics, what is the term for an obstacle to be solved?
- Question
- Issue
- Problem ✅
- Solution
Explanation:
A problem is an issue or barrier that needs a solution through analysis.
45. Fill in the blank: As a data analyst considering problems that involve people and their behaviors and activities, it’s important to take into account the complicated _____ that could create bias in conclusions.
- social context ✅
- company politics
- performance
- attendance habits
Explanation:
Social context includes cultural, economic, and societal dynamics that may influence behaviors and how data should be interpreted to avoid biased conclusions.
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