Ask Questions to Make Data-Driven Decisions Quiz Answers

Get All Weeks Ask Questions to Make Data-Driven Decisions Quiz Answers

Ask Questions to Make Data-Driven Decisions Week 01 Quiz Answers

Practice Quiz-1 Answers

L2 Take action with data:

Q1. A data analytics team works to recognize the current problem. Then, they organize available information to reveal gaps and opportunities. Finally, they identify the available options. These steps are part of what process?

• Using structured thinking
• Categorizing things
• Making connections
• Applying the SMART methodology

Q2. In which step of the data analysis process would an analyst ask questions such as, “What data errors might get in the way of my analysis?” or “How can I clean my data so the information I have is consistent?”

• Ask
• Process
• Prepare
• Analyze

Q3. A data analyst has entered the analysis step of the data analysis process. Identify the questions they might ask during this phase. Select all that apply.

• What story is my data telling me?
• How can I create an engaging presentation to stakeholders?
• How will my data help me solve this problem?
• What is the question I’m trying to answer?.

Q4. A data analyst is trying to understand their target audience. They’re asking questions such as, “How can learning more about my target audience help me figure out how to solve this problem?” and “What research do I need to do about my target audience?” The data analyst is in which phase of the data analysis process?

• Act
• Share
• Ask
• Prepare

Practice Quiz-2 Answers

L3 Solve problems with data:

Q1. A data analyst identifies keywords from customer reviews and labels them as positive or neutral. This an example of which problem type?

• Finding patterns
• Making predictions
• Identifying themes
• Categorizing things

Q2. The spotting something unusual problem type could involve which of the following scenarios?

• A data analyst at an arts nonprofit classifies similar data points into groups for further analysis.
• A data analyst working for an agricultural company examines why a dataset has a surprising and rare data point.
• A data analyst at a clothing retailer creates a list of common topics, categorizes them, and groups each category into a broader subject area for further analysis.
• Data insight helps a landscaping company envision what will happen in the future

Q3. A data analyst at an online retailer looks at trends in historical sales data. They want to understand what happened in the past and, therefore, is likely to happen again in the future. This an example of which problem type?

• Finding patterns
• Making predictions
• Categorizing things
• Identifying themes

Practice Quiz-3 Answers

L4 Craft effective questions:

Q1. A data analyst uses the SMART methodology to create a question that encourages change. This type of question can be described How?

• Results-focused
• Stimulating
• Motivational
• Action-oriented

Q2. A time-bound SMART question specifies which of the following parameters?

• The topic or subject of the analysis
• The desired change the analysis should produce
• The metrics or measures related to the analysis
• The era, phase, or period of analysis

Q3. A data analyst working for a mid-sized retailer is writing questions for a customer experience survey. One of the questions is: “Do you prefer online or in-store?” Then, they rewrite it to say: “Do you prefer shopping at our online marketplace or shopping at your local store?” Describe why this is a more effective question.

• The first question is leading, whereas the second question could have many different answers.
• The first question is closed-ended, whereas the second question encourages the respondent to elaborate.
• The first question is vague, whereas the second question includes important context.
• The first question contains slang that might not make sense to everyone, whereas the second question is easily understandable.

Q4. A data analyst at a social media company is creating questions for a focus group. They use common abbreviations such as PLS for “please” and LMK for “let me know.” This is fair because the participants use social media a lot and are likely to be technically savvy.

• True
• False

Ask Questions to Make Data-Driven Decisions Weekly Challenge 1 Answers

Q1. Structured thinking involves which of the following processes? Select all that apply.

• Organizing available information
• Recognizing the current problem or situation
• Asking SMART questions
• Revealing gaps and opportunities

Q2. The preparation step of the data analysis process involves defining the problem you’re trying to solve and understanding stakeholder expectations.

• True
• False

Q3. The share phase of the data analysis process typically involves which of the following activities? Select all that apply.

• Putting analysis into action to solve a problem
• Creating a slideshow to present to stakeholders
• Summarizing results using data visualizations
• Communicating findings

Q4. A garden center wants to attract more customers. A data analyst in the marketing department suggests advertising in popular landscaping magazines. This is an example of what practice?

• Developing a data analytics case study
• Collecting customer information
• Monitoring social media feedback
• Reaching your target audience

Q5. A data analyst is working for a local power company. Recently, many new apartments have been built in the community, so the company wants to determine how much electricity it needs to produce for the new residents in the future. A data analyst uses data to help the company make a more informed forecast. This is an example of which problem type?

• Spotting something unusual
• Discovering connections
• Identifying themes
• Making predictions

Q6. Describe the key difference between the problem types of categorizing things and identifying themes.

• Categorizing things involves determining how items are different from each other. Identifying themes brings different items back together in a single group.
• Categorizing things involves assigning items to categories. Identifying themes takes those categories a step further, grouping them into broader themes.
• Categorizing things involves assigning grades to items. Identifying themes involves creating new classifications for items.
• Categorizing things involves taking inventory of items. Identifying themes deals with creating labels for items.

Q7. Which of the following examples are closed-ended questions? Select all that apply.

• What are your thoughts about math?
• Is math your favorite subject?
• What grade did you get in your math class?
• How old are you?

Q8. The question, “Why don’t our employees complete their timesheets each Friday by noon?” is not action-oriented. Which of the following questions are action-oriented and more likely to lead to change? Select all that apply.

• What functionalities would make our timesheet web page more user-friendly?
• What features could we add to our calendar app as a weekly timesheet reminder to employees?
• Why don’t employees prioritize filling out their timesheets by noon on Fridays?
• How could we simplify the time-keeping process for our employees?

Q9. In the SMART methodology, time-bound questions are simple, significant, and focused on a single topic or a few closely related ideas.

• True
• False

Q10. Which of the following questions make assumptions? Select all that apply.

• It must be frustrating waiting on hold for so long, right?
• Wouldn’t you agree that product A is better than product B?
• Did you get through to customer service?
• Keeping employees engaged is important, isn’t it?

Ask Questions to Make Data-Driven Decisions Week 02 Quiz Answers

Practice Quiz-1 Answers

L2 Understand the power of data:

Q1. What is the difference between qualitative and quantitative data?

• Qualitative data describes the kind of data being analyzed. Quantitative data describes how much data is being analyzed.
• 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 can be used to measure qualities and characteristics. Quantitative data can be used to measure numerical facts.

Q2. Fill in the blank: Data-inspired decision-making deals with exploring different data sources to find out _____.

• how they can drive business decisions
• if they are based on facts or opinions
• what they have in common
• how they have changed over time

Q3. Which of the following examples describes using data to achieve business results? Select all that apply.

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

Q4. If someone is describing their feelings or emotions, it is qualitative data.

• True
• False

Practice Quiz-2 Answers

L3 Follow the evidence:

Q1. Fill in the blank: Pivot tables in data processing tools are used to _____ data.

• populate
• clean
• validate
• summarize

Q2. In data analytics, how are dashboards different from reports?

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

Q3. Describe the difference between data and metrics.

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

Q4. Return on Investment (ROI) uses which of the following metrics in its definition?

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

Practice Quiz-3 Answers

L4 Connecting the data dots:

Q1. Describe the key differences between small data and big data. Select all that apply.

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

Q2. Which of the following is an example of small data?

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

Q3. The amount of exercise time to burn a minimum of 400 calories is a problem that requires big data.

• True
• False

Ask Questions to Make Data-Driven Decisions Weekly Challenge 2 Answers

Q1. Fill in the blank: In data analytics, a process or set of rules to be followed for a specific task is _____.

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

Q2. Fill in the blank: In data analytics, qualitative data _____. Select all that apply.

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

Q3. In data analytics, reports use live, incoming data from multiple datasets; dashboards use static collections of data.

• True
• False

Q4. 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
• Calculate totals from the data
• Clean data
• Reorganize data

Q5. A metric is a single, quantifiable type of data that can be used for what task?

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

Q6. Fill in the blank: A _____ goal is measurable and evaluated using single, quantifiable data.

• metric
• finite
• benchmark
• conceptual

Q7. 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

Q8. 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

Ask Questions to Make Data-Driven Decisions Week 03 Quiz Answers

Practice Quiz-1 Answers

L2 Working with spreadsheets:

Q1. To sort and filter the data in a spreadsheet, data analysts must use multiple formulas.

• True
• False

Q2. Which time-saving tool do data analysts use to organize data and perform calculations?

• Calculator
• Paper
• Spreadsheet
• Graph

Q3. Within a spreadsheet, data analysts use which tools to save time and effort by automating commands? Select all that apply.

• Tables
• Filters
• Functions
• Formulas

Practice Quiz-2 Answers

L3 Using formulas in spreadsheets:

Q1. Which of the following are examples of operators used in formulas? Select all that apply. 1 / 1 point

• Hyphen (-)
• Forward slash (/)
• Asterisk (*)
• Plus-minus (±)

Q2. In a spreadsheet, a function should always start with which of the following operators?

• Dash (—)
• Plus-minus (±)
• Equal sign (=)
• Colon (:)

Q3. What is the term for the set of cells that a data analyst selects to include in a formula?

• Cell domain
• Data boundary
• Cell set
• Data range

Q4. In a formula, the plus sign (+) is the operator for addition, and the plus-minus (±) is the operator for subtraction.

• True
• False

Q5. If the cells in a spreadsheet contain anything other than numbers, which of the following errors might occur?

• #NAME?
• #DIV/0!
• #VALUE!
• #MIN/5!

Practice Quiz-3 Answers

L5 Save time with structured thinking:

Q1. Fill in the blank: In order to save time and money, a data analyst defines the _____ at the start of a project. Select all that apply.

• timeline
• problem domain
• key milestones
• solution

Q2. The outline used to define a data analyst’s contribution to a project is called what?

• Action plan
• Scope of work
• To-do list
• Diagram

Q3. To address a vague, complex problem, data analysts break it down into smaller steps. They use a process that helps them recognize the current problem or situation. Then, they organize available information, reveal gaps and opportunities, and identify the options. What process does this scenario describe?

• Structured thinking
• Analytical thinking
• Gap analysis
• Data-driven decision-making

Ask Questions to Make Data-Driven Decisions Weekly Challenge 3 Answers

Q1. Both formulas and functions in spreadsheets begin with what symbol?

• Vertical line (|)
• Equals sign (=)
• Plus-minus sign (±)
• Lowercase x

Q2. Attributes are used in spreadsheets for what purpose?

• Label the data in each column
• Insert data into each column
• Analyze the data in a row
• Add a new column

Q3. Which of the following tasks might be performed using spreadsheets?

• Land a new client
• Develop communication skills
• Maintain information about accounts
• Write a sales pitch

Q4. Fill in the blank: Combining formulas and functions enables the function to run based on a _____ set by the formula.

• change
• cell
• count
• criteria

Q5. Which of the following statements describes a key difference between formulas and functions?

• Formulas are used in graphs, and functions are not.
• Formulas span two or more cells, and functions exist in only one cell.
• Formulas contain words and numbers, and functions contain numbers only.
• Formulas are written by the user, and functions are already defined.

Q6. Fill in the blank: Putting data into context helps data analysts eliminate _____.

• fairness
• intolerance
• labels
• bias

Q7. Defining the problem domain is part of which data analytics process?

• Balanced thinking
• Logical thinking
• Organized thinking
• Structured thinking

Q8. A data analyst uses structured thinking to recognize the current problem or situation. Select the final step to structured thinking.

• Identify options
• Monitor options
• Clean data
• Sort data

Ask Questions to Make Data-Driven Decisions Week 04 Quiz Answers

Practice Quiz-1 Answers

L2 Balance team and stakeholder needs:

Q1. As a data analyst, it’s important to communicate often. Sharing detailed notes, creating reports, and using a changelog are all ways to communicate with the people who have invested time and resources in a project. Who are these people?

• Executives
• Customer-facing team
• Stakeholders
• Subject-matter experts

Q2. The customer-facing team does which of the following activities? Select all that apply.

• Share customer feedback
• Compile information about customer expectations
• Tell the data story to others
• Provide operational leadership for the company

Q3. The human resources director approaches a data analyst to propose a new data analysis project. The analyst has a lot of experience in human resources and believes the director is taking the wrong approach, and it will lead to some problems. Select the data analyst’s best course of action.

• Complete the project as requested, but set aside some time in the future to fix the problems that are sure to come up.
• Tell the director that they’re very sorry, but they can’t work on the project.
• Respectfully explain their viewpoints and offer the director some additional information to help improve the project.
• Politely explain that they’re too busy to take on another project at this time.

Practice Quiz-2 Answers

L3 Communication is key:

Q1. To communicate clearly with stakeholders and team members, there are four key questions data analysts ask themselves. The first is: Who is my audience? Identify the remaining three questions. Select all that apply.

• Why are stakeholders and team members important?
• What does my audience need to know?
• What does my audience already know?
• How can I communicate effectively to my audience?

Q2. You’re working on a data analysis project, and you run into an obstacle. You try to find a solution, but you’re having no luck, and now the project is going off schedule. The best course of action is to put in extra hours to keep looking for a solution, rather than bothering your team with the problem.

• True
• False

Q3. A colleague sent you a question via email nearly two days ago. You know it’s going to take a while for you to find the answer because you need to do some research first. You’re too busy to get it done today. What’s the best course of action?

• Reply with a quick update thanking the sender for their patience and letting them know when they can expect you to respond with the answer to their question.
• Forward the email to the entire data analytics team, and ask if someone else can answer the question for you.
• Delete the email. By the time you’re able to answer the question, it won’t be helpful information anyway.
• Respond right away with your best guess to the answer to their question. The sender has been waiting nearly 48 hours, and any response is better than nothing.

Q4. Focusing on stakeholder expectations enables data analysts to achieve what goals? Select all that apply.

• Improve communication among teams
• Build trust
• Understand project goals
• Multitask more effectively

Q5. Setting realistic stakeholder expectations at every stage of a project might involve which of the following tasks? Select all that apply.

• Preparing a report that shows stakeholders the pros and cons of an update to the project
• Creating a reasonable timeline and sharing it with stakeholders
• Keeping problems to yourself so stakeholders don’t have to worry about them
• Communicating to stakeholders any changes that may affect the analysis

Practice Quiz-3 Answers

L4 Recognize data limitations:

Q1. A stakeholder has asked a data analyst to produce a report very quickly. What are some strategies the analyst can apply to ensure their work isn’t rushed, answers the right question, and delivers useful results? Select all that apply.

• Reframe the question
• Work overtime to get the report done by the following day
• Set clear expectations about the timeframe
• Outline the problem

Q2. If a sample size is too small, a few unusual responses can skew the results. To avoid this problem, data analysts aim to collect lots of data and chart trends over longer time periods.

• True
• False

Q3. Asking questions including, “Does my analysis answer the original question?” and “Are there other angles I haven’t considered?” enable data analysts to accomplish what tasks? Select all that apply.

• Use data to get to a solid conclusion
• Help their team make informed, data-driven decisions
• Consider the best ways to share data with others
• Identify primary and secondary stakeholders

Ask Questions to Make Data-Driven Decisions Weekly Challenge 4 Answers

Q1. A data analytics team is working on a project to measure the success of a company’s new financial strategy. The vice president of finance is most likely to be the _____.

• project manager
• analyst
• secondary stakeholder
• primary stakeholder

Q2. A data analyst is researching the buying behavior of people who shop at a company’s retail store and those who might shop there in the future. During the analysis, it will be important to stay in communication with the team that most often interacts with these shoppers. What is the name of this team?

• Project management team
• Executive team
• Data science team
• Customer-facing team

Q3. To communicate clearly with stakeholders and team members, there are four key questions data analysts ask themselves. One of them is: What does my audience need to know? Identify the remaining three questions. Select all that apply.

• How can I communicate effectively to my audience?
• What does my audience already know?
• Who is my audience?
• Why are stakeholders and team members important?

Q4. A data analyst feels overworked. They often stay late to finish work and have started missing deadlines. Their supervisor emails them another project to complete, and this causes the analyst even more stress. How should they handle this situation?

• Respond immediately, letting the supervisor know the expectations at this company are unreasonable.
• Accept the new project right away and hope to not miss another deadline.
• Walk into the supervisor’s office and tell them to give the project to someone else.
• Wait a few minutes to think it over, then respond with a meeting request to discuss this project and the general workload.

Q5. Data analysts pay attention to sample size in order to achieve what goals? Select all that apply.

• To make sure a few unusual responses don’t skew results
• To make sure the data represents a diverse set of perspectives
• To avoid a small sample size leading to inaccurate judgments
• To fully understand the scope of the analytics project

Q6. A data analyst has been invited to a meeting. They review the agenda and notice that their data analysis project is one of the topics that will be discussed. They plan to arrive on time and have a pen and paper to take notes. However, they do not spend time considering project updates they could share or questions they may be asked. This is okay because they’re not the ones running the meeting.

• True
• False

Q7. Which of the following steps are key to leading a professional online meeting? Select all that apply.

• Maintaining control of the meeting by keeping everyone else on mute.
• Sitting in a quiet area that’s free of distractions
• Keeping an eye on your inbox during the meeting in case of an important email
• Making sure your technology is working properly before starting the meeting

Q8. Conflict is a natural part of working on a team. What are some ways to help shift a situation from problematic to productive? Select all that apply.

• Identify the person who caused the issue so they can take responsibility.
• Ask for a conversation to help you better understand the big picture.
• Take a moment to check your emotions before engaging in an argument.
• Reframe the question by asking, “How can I help?”

Next Course Quiz Answers >>

Ask Questions to Make Data-Driven Decisions

<< Previous Course Quiz Answers

Foundations: Data, Data, Everywhere

All Course Quiz Answers of Google Data Analytics Professional Certificate

Course 01: Foundations: Data, Data, Everywhere

Course 02: Ask Questions to Make Data-Driven Decisions

Course 03: Prepare Data for Exploration

Course 04: Process Data from Dirty to Clean

Course 05: Analyze Data to Answer Questions

Course 06: Share Data Through the Art of Visualization

Course 07: Data Analysis with R Programming

Course 08: Google Data Analytics Capstone: Complete a Case Study