Module 1: The Importance of Integrity Answers (Part 1: Q1–15)

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In this post, I provide accurate answers and detailed explanations for Module 1: The importance of integrity of Course 4: Process Data from Dirty to Clean – 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 data integrity and analytics objectives

Practice Quiz

1. Which of the following principles are key elements of data integrity? Select all that apply.

  • Trustworthiness ✅
  • Accuracy ✅
  • Consistency ✅
  • Selectivity

Explanation:
Data integrity refers to maintaining and ensuring the accuracy, consistency, and trustworthiness of data throughout its lifecycle. These principles ensure that data is reliable and usable for analysis. “Selectivity” is not a core principle of data integrity.

2. Which process do data analysts use to make data more organized and easier to read?

  • Data manipulation ✅
  • Data uniformity
  • Data transfer
  • Data replication

Explanation:
Data manipulation involves organizing, transforming, and structuring data to make it more comprehensible and suitable for analysis. Processes like sorting, filtering, and cleaning fall under this category. The other options (data uniformity, transfer, and replication) do not directly address making data easier to read.

3. Before analysis, a company collects data from countries that use different date formats. Which of the following updates would improve the data integrity?

  • Change all of the dates to the same format ✅
  • Organize the data by country
  • Remove data in an unfamiliar date format
  • Leave the dates in their current formats

Explanation:
Standardizing date formats ensures consistency and accuracy in the dataset, which is critical for reliable analysis. Leaving dates in their current format or removing data would compromise integrity, and organizing data by country does not address the format inconsistency issue.

Test your knowledge on insufficient data

Practice Quiz

4. What should an analyst do if they do not have the data needed to meet a business objective? Select all that apply.

  • Create and use hypothetical data that aligns with analysis predictions.
  • Gather related data on a small scale and request additional time to find more complete data. ✅
  • Continue with the analysis using data from less reliable sources.
  • Perform the analysis by finding and using proxy data from other datasets. ✅

Explanation:
If the required data isn’t available, analysts should either gather related data on a small scale while requesting more time or use proxy data, which can serve as a substitute for missing information. Creating hypothetical data compromises the integrity of the analysis, and using data from unreliable sources introduces inaccuracies and bias.

5. Which of the following are limitations that might lead to insufficient data? Select all that apply.

  • Outdated data ✅ 
  • Duplicate data
  • Data that updates continually ✅
  • Data from a single source ✅

Explanation:

  • Outdated data: Data that is no longer current may not reflect the present situation or trends, making it less useful for analysis.
  • Data that updates continually: While it provides real-time insights, continually updating data can be challenging to manage and may result in incomplete datasets if not captured properly.
  • Data from a single source: Relying on one source of data limits diversity and comprehensiveness, which can lead to incomplete or biased analysis.

6. A data analyst wants to find out how many people in Utah have swimming pools. It’s unlikely that they can survey every Utah resident. Instead, they survey enough people to be representative of the population. This describes what data analytics concept?

  • Statistical significance
  • Confidence level
  • Margin of error
  • Sample ✅

Explanation:
A sample is a subset of a population that is surveyed or analyzed to infer information about the entire population. This approach allows analysts to gather insights without needing to collect data from every individual, making it a practical and efficient method in data analytics.

Test your knowledge on testing your data

Practice Quiz

7. A research team runs an experiment to determine if a new security system is more effective than the previous version. What type of results are required for the experiment to be statistically significant?

  • Results that are real and not caused by random chance ✅
  • Results that are unlikely to occur again
  • Results that are hypothetical and in need of more testing
  • Results that are inaccurate and should be ignored

Explanation:
Statistical significance indicates that the results of an experiment are unlikely to have occurred due to random variation or chance. It ensures that the observed effect or difference is genuine and meaningful for decision-making.

8. In order to have a high confidence level in a customer survey, what should the sample size accurately reflect?

  • The trends from other customer surveys
  • The entire population ✅
  • The most valuable members of the population
  • The predictions of stakeholders

Explanation:
A sample size must accurately reflect the entire population to ensure the survey results are representative. This minimizes bias and increases the reliability of conclusions drawn from the data.

9. A data analyst determines an appropriate sample size for a survey. They can check their work by making sure the confidence level percentage plus the margin of error percentage add up to 100%.

  • True
  • False ✅

Explanation:
The confidence level and margin of error are independent measures. The confidence level indicates the probability that the true population parameter lies within the margin of error, while the margin of error defines the range of values. They do not sum up to 100%; instead, they complement each other in interpreting survey accuracy.

Test your knowledge on margin of error

Practice Quiz

10. Fill in the blank: Margin of error is the _____ amount that the sample results are expected to differ from those of the actual population.

  • minimum
  • median
  • maximum ✅
  • average

Explanation:
Margin of error represents the maximum expected difference between the observed results in a sample and the true population parameter. It accounts for variability and ensures that the actual value is within this range with a specified confidence level.

11. In a survey about a new cleaning product, 75% of respondents report they would buy the product again. The margin of error for the survey is 5%. Based on the margin of error, what percentage range reflects the population's true response?

  • Between 73% and 78%
  • Between 70% and 80% ✅
  • Between 70% and 75%
  • Between 75% and 80%

Explanation:
The margin of error (5%) is added to and subtracted from the survey result (75%) to calculate the range:

  • Lower Bound: 75%−5%=70%75\% – 5\% = 70\%
  • Upper Bound: 75%+5%=80%75\% + 5\% = 80\%

Thus, the true response of the population is expected to fall within 70% to 80% with the specified confidence level.

Module 1 challenge

Graded Quiz

12. Fill in the blank: If a data analyst is using data that has been _____, the data will lack integrity and the analysis will be faulty.

  • wide
  • compromised ✅
  • public
  • clean

Explanation:
If data is altered, corrupted, or incomplete, it’s considered compromised, making any analysis based on it unreliable.

13. A financial analyst imports a dataset to their computer from a storage device. As it’s being imported, the connection is interrupted, which compromises the data. Which of the following processes caused the compromise?

  • Data analysis
  • Data gathering
  • Data manipulation
  • Data transfer ✅

Explanation:
If a file gets corrupted or interrupted during movement (e.g., USB to PC), it’s a transfer issue.

14. A data analyst is given a dataset for analysis. It includes data about the total population of every country in the previous 20 years. Based on the available data, an analyst would be able to determine the reasons behind a certain country's population increase from 2016 to 2017.

  • True
  • False ✅

Explanation:
The dataset only has population counts, not causes or reasons behind changes. Additional context is needed.

15. 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.

Which of the following has duplicate data?

  • Data for Symteco on 2/21/2014
  • Data for Symteco on 5/20/2014
  • Data for Valando on 2/18/2014 ✅
  • Data for Valando on 1/1/2014

Explanation:
Duplicate entries repeat the same values for the same entity and time, which could skew results or cause errors.

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

Next Part: Module 1: The Importance of Integrity Answers (Part 2: Q16–30)

Part 2: Q16–30

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