Module 1: The Importance of Integrity Answers (Part 3: Q31–48)

This is Part 3 of the Module 1 quiz answers for “The Importance of Integrity ” from the Google Data Analytics Professional Certificate on Coursera.

Here, we’ll walk through questions 31 to 38 with detailed explanations to support your learning.

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

31. A car manufacturer wants to learn more about the brand preferences of electric car owners. There are millions of electric car owners in the world. Who should the company survey?

  • A sample of all electric car owners ✅
  • The entire population of electric car owners
  • A sample of car owners who have owned more than one electric car
  • A sample of car owners who most recently bought an electric car

Explanation:
A representative sample of all electric car owners ensures the survey captures diverse brand preferences across the entire population.

32. A candy manufacturer finds an even distribution of sales across all age ranges of customers who purchase their products. The manufacturer decides to conduct a survey to learn more about its customer base. Due to age requirements, they can only send the survey to customers who are 21 years or older. This scenario can be described as what?

  • Down sampling bias
  • Sampling bias ✅
  • Unbiased sampling
  • Upsampling bias

Explanation:
Since only customers 21 or older can be surveyed, younger customers are excluded. This creates sampling bias, where not all segments of the population are equally represented.

33. What best describes a sample size?

  • A subset of the population between the 25th and 50th percentile
  • A random subset of the population
  • A subset that is representative of the population as a whole ✅
  • A subset of the population excluding outliers

Explanation:
A representative sample accurately reflects the population’s characteristics, ensuring reliable analysis and conclusions.

34. Fill in the blank: In order to have a strong and thorough analysis, a data analyst must verify _____.

  • data replication
  • data manipulation
  • data engineering
  • data integrity ✅

Explanation:
Data integrity means ensuring the accuracy, consistency, and reliability of data throughout its lifecycle. It’s essential for making correct decisions based on the data.

35. Fill in the blank: _____ is the process of changing data to make it more organized and easier to read.

  • Data transfer
  • Data manipulation ✅
  • Data gathering
  • Data replication

Explanation:
Data manipulation refers to formatting, sorting, and modifying data so it’s organized and easier to analyze.

36. You are working for a global technology company. You have a dataset with the company’s total cell phone sales by country from 2015 to present. Based on the data you have, what questions are you able to answer?

  • What was the effect on sales when a new phone model was launched?
  • What was the effect on sales when new phone features were introduced?
  • What countries have the most cell phone sales in the past three years? ✅
  • What are the mean cell phone sales for each country since 2010?

Explanation:
The question must be based only on the available data, which spans 2015 to the present. You can’t answer questions about events (like new features) unless they are clearly marked in the data.

37. A data analyst, working for a publishing company, gathers a dataset which includes all books sold in the United Kingdom over the last three years. However, they decide to generate new data that represents global book sales. What type of insufficient data does this scenario describe?

  • Data that keeps updating
  • Data that is outdated
  • Data that is geographically limited ✅
  • Data from only one source

Explanation:
Using only UK sales data to represent global sales is inaccurate. This is an example of data that is geographically limited.

38. A company is trying to learn more about their customer base. They would like to conduct a survey to understand why their customers chose their brand. How should the company survey its customers?

  • Conduct a survey of customers who purchased a different brand
  • Conduct a survey of customers that live in high-income areas
  • Conduct a survey with a representative sample of their customer population ✅
  • Conduct a survey with customers who have purchased more than five products

Explanation:
To get meaningful insights, surveys must include a diverse cross-section of the entire customer base—not just high-income areas or frequent buyers.

39. Sometimes during analysis, an analyst discovers that it’s necessary to adjust the business objective. When this happens, the analyst should take the initiative to do so without involving others in order to be respectful of their time.

  • True
  • False ✅

Explanation:
If the objective changes, it should be discussed with stakeholders. Analysts should collaborate, not make such decisions independently.

40. A car dealership gathers data about their entire customer population. They decide to conduct a survey to understand why their customers chose their dealership. They send out an email to all customers who have purchased more than two vehicles in the past five years. What does this scenario describe?

  • Unbiased sampling
  • Geographically limited sampling
  • Random sampling
  • Sampling bias ✅

Explanation:
Surveying only repeat customers excludes other types of customers and creates sampling bias. It won’t give a complete view of all customers’ reasons.

41. A data analyst needs to migrate data from a server located at their company's headquarters to a remote site. This can lead to what type of data integrity issue?

  • Data replication ✅
  • Data cleaning
  • Data transfer ✅
  • Data manipulation

Explanation:

  • Data transfer: Errors during transfer can cause data loss or corruption.
  • Data replication: Issues like duplicate or inconsistent records may arise when replicating data between systems.

42. As a data analyst, you work with data about the life expectancy of sea turtles in the Coral Triangle. The dataset contains an estimated birthdate and deathdate for all tracked sea turtles. With the data you have, what questions are you able to answer?

  • What is the median age a sea turtle has lived in the Coral Triangle? ✅
  • Where is the most prevalent location sea turtles are being hatched in the Coral Triangle?
  • What is the largest sea turtle ever recorded?
  • Is the sea turtle population increasing throughout the world?

Explanation:
Because the dataset contains birth and death dates, you can calculate age statistics like median age. But you can’t answer questions unrelated to this data.

43. A clothing manufacturer wants to learn more about why their consumers have purchased the brand’s products. How should this manufacturer conduct their survey?

  • Send the survey to a representative sample of their customers ✅
  • Send the survey to customers who have purchased more than one product
  • Send the survey to their least frequent customers
  • Send the survey to random people who buy clothes

Explanation:
A representative sample gives a balanced view of why customers buy the product. Only surveying specific groups would introduce bias.

44. A data analyst wants to predict the production output of a factory using a dataset that covers the years 2020 to 2021. In 2022, the factory implemented major labor and facility changes. What limitation of the data means that the analyst needs to get new data?

  • The data keeps updating.
  • The data is outdated. ✅
  • The data is geographically limited.
  • The data is from only one source.

Explanation:
Since the data doesn’t include 2022 changes (new labor/facility changes), it can’t reliably predict future output. It’s outdated.

45. In the data analysis process, how does a sample relate to a population?

  • A sample is a duplicate selection of data that is taken from the population.
  • A sample is an ideal example taken from a population.
  • A sample is a part of a population that is representative of the population. ✅
  • A sample is an average of all the data that represents the population.

Explanation:
In statistics, a sample is a smaller group taken from a population that should reflect the same characteristics as the whole.

46. Fill in the blank: Data _____ refers to the accuracy, completeness, consistency, and trustworthiness of data throughout its life cycle.

  • sampling
  • integrity ✅
  • analysis
  • replication

Explanation:
Data integrity ensures the data’s reliability and accuracy from collection to usage. It encompasses its completeness, consistency, and trustworthiness throughout its lifecycle.

47. A data analyst is given a dataset for analysis. It includes data about the total population of every country in the previous 20 years. Which of the following questions can the analyst use this dataset to address? Select all that apply.

  • What was the average population of a certain country from 2015 through 2020? ✅
  • What was the difference in population between two specific countries in 2018? ✅
  • What was the effect of migration on the population of a certain country?
  • What was the reason for the population increase in a certain country?

Explanation:
This dataset contains population data, making it suitable for calculating averages or differences in specific years. However, questions about migration effects or reasons for population changes require additional context beyond raw population data.

48. A high school principal is estimating the total number of students that will attend an upcoming event. She assumes that the older students are unlikely to attend and decides to only survey the first-year students. What issue will the principal face when calculating her estimation?

  • The sample is too small.
  • The sample should be the older students.
  • The sample exhibits sampling randomness.
  • The sample exhibits sampling bias. ✅

Explanation:
Surveying only first-year students introduces sampling bias, as it excludes older students who may also attend the event. A representative sample is necessary for accurate estimations.

Part 2 (Q16–30)

Congratulations! You’ve completed all questions. Share this post if it helped you, and check out other Coursera quiz answers below.

Related contents:

Module 2: Clean data for more accurate insights
Module 3: Data cleaning with SQL
Module 4: Verify and report on cleaning results
Module 6: Course wrap-up

You might also like:

Course 1: Foundations: Data, Data, Everywhere
Course 2: Ask Questions to Make Data-Driven Decisions
Course 3: Prepare Data for Exploration
Course 5: Analyze Data to Answer Questions
Course 6: Share Data Through the Art of Visualization
Course 7: Data Analysis with R Programming
Course 8: Google Data Analytics Capstone: Complete a Case Study

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