Module 1: The Importance of Integrity Answers (Part 2: Q16–30)
This is Part 2 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 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. A data analyst at a nonprofit organization is working with a dataset about a summer fundraiser. Although they have a lot of useful data by the end of the month, they recognize that the data is insufficient. So, they decide to wait until the end of the season to begin working with the dataset. Which type of insufficient data does this example describe?
- Outdated data
- Data from only one source
- Geographically limited data
- Data that keeps updating ✅
Explanation:
If data is still being collected or changing, it’s incomplete, and analysis should wait until it’s finalized.
17. When gathering data through a survey, companies can save money by surveying 100% of a population.
- True
- False ✅
Explanation:
Surveying everyone is expensive and time-consuming. Using a well-chosen sample is more efficient.
18.Fill in the blank: Sampling bias in data collection happens when a sample isn’t representative of _____.
- the population as a whole ✅
- a dataset about the population
- a subset of the population
- the population most affected by the data
Explanation:
If your sample doesn’t match the full population’s diversity, your results won’t be accurate.
19. Data and business objectives might not align for a number of reasons. Which of the following issues can prevent alignment? Select all that apply.
- Sampling bias ✅
- Data integrity
- Data visualization
- Insufficient data ✅
Explanation:
Poor quality or missing data can lead to wrong insights, which misaligns with the company’s actual goals.
Data visualization helps interpretation, not alignment. Integrity supports alignment.
20. Which of the following conditions are necessary to ensure data integrity? Select all that apply.
- Privacy
- Completeness ✅
- Statistical power
- Accuracy ✅
Explanation:
Completeness ensures no important data is missing.
Accuracy ensures the data is correct.
Privacy is about security, not integrity. Statistical power relates to hypothesis testing.
21. What is one potential problem associated with data manipulation that analysts must be aware of?
- Data manipulation can separate a dataset among different locations.
- Data manipulation can help organize a dataset.
- Data manipulation can introduce errors. ✅
- Data manipulation can make a dataset easier to read.
Explanation:
While helpful, it can also lead to mistakes—for example, incorrect formulas, misapplied filters, or wrong transformations.
22. As a data analyst, you are working for a national pizza restaurant chain. You have a dataset with monthly order totals for each branch over the past year. With only this data, what questions can you answer?
- Which region had the highest sales over the last two years?
- Which branch will be the most profitable over the next year?
- What was the most popular item on the menu?
- Which branch had the most orders in the last month of last year? ✅
Explanation:
You can only answer what the data tells you—order totals by branch and time. You can’t predict the future or find the most popular menu item unless that info is included.
23. A data analyst is given a dataset for analysis. To use the template for this dataset, click the link below and select “Use Template.”
Link to template: June 2014 Invoices
OR
If you don’t have a Google account, download the CSV file directly from the attachment below.
June 2014 Invoices - Sheet1
The data analyst is asked to find the average estimate for Symteco over the past three years. What limitation of the data makes this impossible?
- The data uses the wrong currency.
- The data is all from a single year. ✅
- The data does not include Symteco.
- The data does not include estimates.
Explanation:
To calculate a 3-year average, you need 3 years’ worth of data.
24. A data analyst at a software company wants to learn more about industry competitors. Because the software industry has more mergers than any other field, the companies and their products are constantly evolving. The analyst has a dataset from three years ago, and they notice that many of the companies and products in the dataset have changed. What makes the analyst decide that the data is insufficient, so they should generate fresh data instead?
- It is outdated data. ✅
- It is geographically limited data.
- It is data that keeps updating.
- It is data from only one source.
Explanation:
Data that is outdated no longer reflects current conditions, especially in a fast-changing industry like software. Fresh data is required to ensure relevance and accuracy.
25. A restaurant gathers data about a new dish by providing free samples to parties of six or more diners. What does this scenario describe?
- Random sampling
- Unbiased sampling
- Geographically limited sampling
- Sampling bias ✅
Explanation:
By only sampling large groups, the restaurant excludes smaller dining groups, which may think differently.
26. Which of the following processes helps ensure a close alignment of data and business objectives?
- Completing data replication
- Transferring data multiple times
- Maintaining data integrity ✅
- Having data update automatically during analysis
Explanation:
If your data is accurate, complete, and trustworthy, you’ll get insights that match business needs.
27. What can jeopardize data integrity throughout its lifecycle? Select all that apply.
- Insufficient data
- Human error ✅
- Malware ✅
- System failures ✅
Explanation:
All of these can corrupt, delete, or alter data, making it unusable or untrustworthy.
28. A healthcare company keeps copies of their data at several locations across the country. The data becomes compromised because each location creates a copy of the original at different times of day. Which of the following processes caused the compromise?
- Data gathering
- Data manipulation
- Data transfer
- Data replication ✅
29. 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 would the analyst need more data to address?
- Which country had the smallest population in 2017?
- Which country had the greatest population in 2015?
- What was the reason for the population increase in a certain country? ✅
- What was the population of a certain country in 2020?
Explanation:
Data replication is the process of copying and storing data in multiple locations. While it helps with redundancy and availability, if not properly synchronized, it can lead to data inconsistency.
In this case, each location created a copy at different times of the day, which led to out-of-sync copies and potential data conflict or corruption — thus compromising the integrity of the data. This is a classic issue with unsynchronized or poorly managed replication.
30. A data analyst is given a dataset for analysis. To use the template for this dataset, click the link below and select “Use Template.”
Link to template: June 2014 Invoices
OR
If you don’t have a Google account, download the CSV file directly from the attachment below.
June 2014 Invoices - Sheet1
Which of the following are limitations of this dataset?
- Identifying the most profitable clients between January and November of 2014 ✅
- Identifying the least profitable clients between January and November of 2014 ✅
- Identifying the worst paying client between March and December of 2014 ✅
- Identifying the best paying client between January and November of 2014
Explanation:
The dataset is limited because it only covers June 2014 invoices, making it insufficient for analyzing clients’ profitability or payments across a broader time frame.
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