Module 5: Endless Career Possibilities Answers (Part 1: Q1–15)

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In this post, I provide accurate answers and detailed explanations for Module 5: Endless career possibilities of Course 1: Foundations: Data, Data, Everywhere – Google Data Analytics Professional Certificate.

Whether you’re preparing for quizzes or brushing up on your knowledge, these insights will help you master the concepts effectively. Let’s dive into the correct answers and detailed explanations for each question.

Here, we’ll walk through questions 1 to 15 with detailed explanations to support your learning.

To find answers to the remaining questions, check out the full module breakdown below:

Test your knowledge on making fair business decisions

Practice Quiz

1. What steps do data analysts take to ensure fairness when collecting data? Select all that apply.

  • Clean the data provided
  • Use an inclusive sample population ✅
  • Understand the social context ✅
  • Include data self-reported by individuals ✅

Explanation:
To ensure fairness, analysts should:

  1. Use inclusive sample populations to represent diverse groups.
  2. Understand the social context to identify potential biases or disparities in the data.
  3. Include self-reported data when possible to reflect the true experiences and identities of individuals.

2. Avens Engineering needs more engineers, so they purchase ads on a job search website. The website’s data reveals that 86% of engineers are men. Based on that number, an analyst decides that men are more likely to be successful applicants, so they target the ads to male job seekers. What should the analyst have done instead?

  • Only show ads for the engineering jobs to women.
  • Decline to accept ads from Avens Engineering because of fairness concerns.
  • Make sure their recommendation doesn’t create or reinforce bias ✅
  • Let Avens Engineering decide which type of applicants to target ads to.

Explanation:
The analyst should avoid reinforcing existing biases, such as targeting ads exclusively to men based on historical data. Instead, they should promote practices that ensure equal opportunities for all qualified candidates, irrespective of gender.

3. On a railway line, peak ridership occurs between 7:00 AM and 5:00 PM. The fairness of a passenger survey could be improved by over-sampling data from which group?

  • Nighttime riders ✅
  • Daytime riders
  • Female passengers
  • Male passengers

Explanation:
Since peak ridership occurs during the daytime, nighttime riders are likely underrepresented in the survey data. Over-sampling nighttime riders would ensure their perspectives are included, leading to a more balanced and fair dataset.

4. A real estate company needs to hire a human resources assistant. The owner asks a data analyst to help them decide where to advertise the job opening. The analyst learns that the majority of human resources professionals are women, validates this finding with research, and targets ads to a women's community college. This is fair because the analyst conducted research to make sure the information about gender breakdown of human resources professionals was accurate.

  • True
  • False ✅

Explanation:
Targeting ads solely to a women’s community college is not fair, even if the research indicates a gender disparity in the profession. Such targeting can perpetuate stereotypes and exclude qualified candidates from other demographics.

*Module 5 challenge*

Graded Quiz

5. An online gardening magazine wants to understand why its subscriber numbers have been increasing. A data analyst discovers that significantly more people subscribe when the magazine has its annual 50%-off sale. This is an example of what?

  • Analyzing consumer preferences using artificial intelligence
  • Analyzing customer buying behaviors ✅
  • Analyzing social media engagement
  • Analyzing the number of customers by calculating daily foot traffic

Explanation:
The analysis focuses on how customers respond to price discounts, which is an example of examining buying behaviors.

6. Fill in the blank: A doctor’s office has discovered that patients are waiting 20 minutes longer for their appointments than in past years. To help solve this problem, a data analyst could investigate how many nurses are on staff at a given time compared to the number of _____.

  • doctors seeing new patients
  • patients with appointments ✅
  • negative comments about the wait times on social media
  • doctors on staff at the same time

Explanation:
Comparing staffing levels with the number of patients helps determine if under-staffing is causing the delays.

7. A problem is an obstacle to be solved, an issue is a topic to investigate, and a question is designed to discover information.

  • True ✅
  • False

Explanation:
This statement accurately describes the distinctions between a problem, issue, and question in data analysis.

8. What is a question or problem that a data analyst answers for a business?

  • Mission statement
  • Hypothesis
  • Complaint
  • Business task ✅

Explanation:
A business task is the key challenge or question a data analyst is trying to solve.

9. Fill in the blank: Data-driven decision-making is described as using _____ to guide business strategy.

  • gut instinct
  • visualizations
  • facts ✅
  • intuition

Explanation:
Facts drawn from data are the foundation of data-driven decision-making, not assumptions or instincts.

10. It’s possible for conclusions drawn from data analysis to be both true and unfair.

  • True ✅
  • False

Explanation:
A conclusion might be based on accurate data but still be unfair if the data itself is biased or incomplete.

11. A data analyst is analyzing fruit and vegetable sales at a grocery store. They’re able to find data on everything except red onions. What’s the best course of action?

  • Ask a teammate for help finding data on red onions. ✅
  • Exclude red onions from the analysis.
  • Exclude all onion varieties from the analysis.
  • Use the data on white onions instead, as they’re both onion varieties.

Explanation:
The best course of action is to try to find the missing data to keep the analysis complete and accurate.

12. Collaborating with a social scientist to provide insights into human bias and social contexts is an effective way to avoid bias in your data.

  • True ✅
  • False 

Explanation:
Social scientists provide insights into bias, context, and fairness, making your analysis more socially responsible.

13. A restaurant hires a data analyst to determine the best times to have the restaurant open. Which of the following methods can the data analyst use to help build a better schedule for the restaurant? Select all that apply.

  • Analyze weekly weather data
  • Analyze staffing levels for different days
  • Examine hourly customer numbers ✅
  • Survey customers on their preferred times to dine ✅

Explanation:
Understanding when customers dine and what they prefer allows analysts to create an optimized schedule.

14. A restaurant has noticed that customers often wait longer in line than in previous years. How could a data analyst help solve this problem?

  • Analyze the average sales amount per customer
  • Analyze customer survey results about the preferred opening hours of the restaurant
  • Analyze the number of staff on shift at any time ✅
  • Analyze the products customers are purchasing

Explanation:
Staffing analysis helps identify whether there are enough employees to manage customer volume effectively.

15. Fill in the blank: A business task is described as the _____ a data analyst answers for a business.

  • solution
  • complaint
  • question ✅
  • comment

Explanation:
A business task is the specific question that analysis is meant to answer.

That’s it for Part 1! Continue your learning journey with the next set of answers.

Next Part: Module 5: Endless Career Possibilities Answers (Part 2: Q16–30)

Part 2: Q16–30

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