Module 2: Make data-driven decisions

Looking for ‘ask questions to make data-driven decisions module 2 answers‘?

In this post, I provide accurate answers and detailed explanations for Module 2: Make data-driven decisions of Course 2: Ask Questions to Make Data-Driven Decisions – 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.

Test your knowledge on the power of data

Practice Quiz

1. What is the difference between qualitative and quantitative data?

  • Qualitative data can be used to measure qualities and characteristics. Quantitative data can be used to measure numerical facts. ✅
  • Qualitative data is specific. Quantitative data is subjective.
  • Qualitative data is about the quality of a product or service. Quantitative data is about how much of that product or service is available.
  • Qualitative data describes the kind of data being analyzed. Quantitative data describes how much data is being analyzed.

Explanation:

  • Qualitative data focuses on non-numerical aspects like qualities, characteristics, or descriptions.
  • Quantitative data involves numerical information that can be measured or counted.

2. Fill in the blank: Data-inspired decision-making can discover _____ when exploring different data sources.

  • what the data has in common ✅
  • which experts can give advice
  • if a decision was properly made
  • where the largest amount of data is

Explanation:
Data-inspired decision-making involves identifying patterns, trends, and commonalities across various data sources to support effective decisions.

3. Which of the following examples describes using data to achieve business results? Select all that apply.

  • A movie theater tracks the number of weekend movie goers for three months.
  • A video streaming service analyzes user preferences to customize movie recommendations. ✅
  • A grocery chain collects data on sale items and pricing from each store.
  • A large retailer performs data analysis on product purchases to create better promotions. ✅

Explanation:

  • These examples show actionable data analysis being applied directly to achieve business outcomes, such as improving recommendations and optimizing promotions.

4. If someone is subjectively describing their feelings or emotions, it is qualitative data.

  • True ✅
  • False

Explanation:
Subjective descriptions of feelings or emotions represent qualitative data, as they capture non-numerical and descriptive information.

Test your knowledge on following the evidence

Practice Quiz

5. Fill in the blank: Pivot tables in data processing tools are used to _____ data.

  • summarize ✅
  • validate
  • clean
  • populate

Explanation:
Pivot tables are a tool used in data analysis to summarize, organize, and analyze data, making it easier to extract meaningful insights from large datasets.

6. In data analytics, how are dashboards different from reports?

  • Dashboards contain static data. Reports contain data that is constantly changing.
  • Dashboards are used to share updates with stakeholders only periodically. Reports give stakeholders continuous access to data.
  • Dashboards monitor live, incoming data from multiple datasets and organize the information into one central location. Reports are static collections of data. ✅
  • Dashboards provide a high-level presentation of historical data. Reports provide a more detailed presentation of live, interactive data.

Explanation:
Dashboards are interactive and display live, real-time data from various sources, while reports are typically static snapshots of data used for periodic updates or analysis.

7. Describe the difference between data and metrics.

  • Data is quantifiable and used for measurement. Metrics are unorganized collections of facts.
  • Data can be used for measurement. Metrics cannot be used for measurement.
  • Data is a collection of facts. Metrics are quantifiable data types used for measurement. ✅
  • Data is quantifiable. Metrics are unquantifiable.

Explanation:
Data is raw, unprocessed information. Metrics are derived from data and represent specific, measurable values, often used to track performance.

8. Return on Investment (ROI) uses which of the following metrics in its definition?

  • Supply and demand
  • Sales and margin
  • Inventory and units
  • Profit and investment ✅

Explanation:
ROI measures the efficiency of an investment by comparing the profit generated to the initial investment cost. The formula is typically:
ROI=ProfitInvestment×100\text{ROI} = \frac{\text{Profit}}{\text{Investment}} \times 100

Test your knowledge on connecting the data dots

Practice Quiz

9. Describe the key differences between small data and big data. Select all that apply.

  • Small data involves datasets concerned with a small number of specific metrics. Big data involves datasets that are larger and less specific. ✅
  • Small data is typically stored in a database. Big data is typically stored in a spreadsheet.
  • Small data focuses on short, well-defined time periods. Big data focuses on change over a long period of time. ✅
  • Small data is effective for analyzing day-to-day decisions. Big data is effective for analyzing more substantial decisions. ✅

Explanation:

  • Small data is focused, specific, and typically used for short-term analysis, such as operational or routine decisions.
  • Big data refers to large, complex datasets that often require advanced tools and techniques for analysis. It is used for long-term trends or substantial decision-making.
  • Storage methods (database vs. spreadsheet) are not a reliable distinction, as both can store small or large datasets depending on their structure.

10. Which of the following is an example of small data?

  • The trade deficit between two countries over a hundred years
  • The number of steps someone walks in a day ✅
  • The bed occupancy rate for a hospital for the past decade
  • The total absences of all high school students

Explanation:

  • This is a small, specific metric tied to an individual, making it an example of small data.
  • The other options involve broader, long-term datasets, such as historical trade deficits, hospital occupancy rates, or school absences, which fall under big data.

11. The amount of exercise time it takes for a single person to burn a minimum of 400 calories is a problem that requires big data.

  • True
  • False ✅

Explanation:

  • This is a small, specific problem and can be addressed using small datasets or even individual metrics, making it a small data problem.
  • Big data typically involves larger-scale analysis across many individuals or datasets, which is unnecessary here.

*Weekly challenge 2*

Graded Quiz

12. Which of the following statements describes an algorithm?

  • A process or set of rules to be followed for a specific task ✅
  • A method for recognizing the current problem or situation and identifying the options
  • A tool that enables data analysts to spot something unusual
  • A technique for focusing on a single topic or a few closely related ideas

Explanation: Algorithms are step-by-step instructions or rules designed to solve a problem or complete a task efficiently.

13. Fill in the blank: If a data analyst is measuring qualities and characteristics, they are considering _____ data.

  • quantitative
  • unbiased
  • cleaned
  • qualitative ✅

Explanation:
Qualitative data captures non-numeric, descriptive attributes such as qualities or characteristics.

14. In data analytics, reports use live, incoming data from multiple datasets; dashboards use static collections of data.

  • True
  • False ✅

15. A pivot table is a data-summarization tool used in data processing. Which of the following tasks can pivot tables perform? Select all that apply.

  • Group data
  • Clean data
  • Calculate totals from data
  • Reorganize data

Explanation:
Pivot tables allow users to summarize, reorganize, and group data for deeper insights.

16. A metric is a single, quantifiable type of data that can be used for what task?

  • Setting and evaluating goals ✅
  • Defining a problem type
  • Cleaning data
  • Sorting and filtering data

17. Which of the following options describes a metric goal? Select all that apply.

  • Evaluated using metrics ✅
  • Indefinite
  • Measurable ✅
  • Based on theory

Explanation:
Metric goals are clearly defined and can be assessed using specific metrics.

18. Fill in the blank: Return on investment compares the _____ of an investment to the net profit gained from that investment.

  • success
  • purpose
  • cost ✅
  • timing

Explanation:
ROI evaluates the profitability of an investment by comparing its cost to the profit it generates.

19. Fill in the blank: A data analyst is using data to address a large-scale problem. This type of analysis would most likely require _____. Select all that apply.

  • small data
  • data that reflects change over time ✅
  • data represented by a limited number of metrics
  • big data ✅

20. Fill in the blank: In data analytics, qualitative data _____. Select all that apply.

  • is always time bound
  • measures qualities and characteristics ✅
  • is subjective ✅
  • measures numerical facts

21. Fill in the blank: A _____ is a data-summarization tool used to sort, reorganize, group, count, total, or average data.

  • report
  • dashboard
  • function
  • pivot table ✅

22. Fill in the blank: A _____ goal is measurable and evaluated using single, quantifiable data.

  • metric ✅
  • finite
  • conceptual
  • benchmark

23. Describe the main differences between big and small data.

  • Small data is typically stored and organized in databases. Big data is typically stored and organized in spreadsheets.
  • Small data is less useful to data analysts. Big data is more useful to data analysts.
  • Small data is specific and concerns a short time period. Big data is less specific and concerns a longer time period. ✅
  • Small data has been cleaned and sorted. Big data has not yet been cleaned or sorted.

Explanation:
Small data is typically focused and short-term, while big data involves larger, more complex datasets spanning longer periods.

24. In data analytics, a pattern is defined as a process or set of rules to be followed for a specific task.

  • True
  • False ✅

25. In data analytics, quantitative data measures qualities and characteristics.

  • True
  • False ✅

26. In data analytics, reports use data that doesn’t change once it’s been recorded. Which of the following terms describes this type of data?

  • Comprehensive
  • Real-time
  • Monitored
  • Static ✅

Explanation:
Static data remains fixed once recorded, making it suitable for reports and historical analysis.

27. Which data-summarization tool do data analysts use to sort, reorganize, group, count, total, or average data?

  • A function
  • A pivot table ✅
  • A dashboard
  • A report

28. A metric is a specific type of data that companies use to identify a problem domain.

  • True
  • False ✅

29. Fill in the blank: A metric goal is a _____ goal set by a company that is evaluated using metrics.

  • finite
  • theoretical
  • conceptual
  • measurable ✅

30. A data analyst is using data from a short time period to solve a problem related to someone’s day-to-day decisions. They are most likely working with small data.

  • True ✅
  • False

31. If a data analyst compares the cost of an investment to the net profit of that investment over a period of time, they’re analyzing the investment scope.

  • True
  • False ✅

32. What is an example of using a metric? Select all that apply.

  • Using column headers to sort and filter data
  • Using annual profit targets to set and evaluate goals ✅
  • Using key performance indicators, such as click-through rates, to measure revenue ✅
  • Using a pie chart to visualize data

Explanation:
Metrics are quantifiable measurements used to evaluate performance against set goals.

33. Fill in the blank: In data analytics, a process or set of rules to be followed for a specific task is _____.

  • a pattern
  • a domain
  • an algorithm ✅
  • a value

34. Fill in the blank: Return on investment compares the cost of an investment to the _____ of that investment.

  • purpose
  • timing
  • net profit ✅
  • future success 

35. In data analytics, dashboards monitor data that is a continuous source of incoming information. Which of the following terms describes this type of data?

  • Comprehensive
  • Live ✅
  • Filtered
  • Sorted

Related contents:

Module 1: Ask effective questions
Module 3: Spreadsheet magic
Module 4: Always remember the stakeholder
Module 4: *Course challenge*

You might also like:

Course 1: Foundations: Data, Data, Everywhere
Course 3: Prepare Data for Exploration
Course 4: Process Data from Dirty to Clean
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

Leave a Reply