Coursera Google Data Analytics Professional Certificate Course 6: Share Data Through the Art of Visualization – Visualize Data quiz answers to all weekly questions (weeks 1 – 4): Show
You may also be interested in Google Data Analytics Professional Certificate Course 1: Foundations – Cliffs Notes. Week 1: Visualizing dataData visualization is the graphical representation of data. In this part of the course, you’ll be introduced to key concepts, including accessibility, design thinking, and other factors that play a role in visualizing the data in your analysis. Learning Objectives
Answers to week 1 quiz questionsL2 Data visualizationQuestion 1Fill in the blank: Correlation charts show _ among data.
Question 2After analyzing their data, a junior analyst creates bar graphs, line graphs, and pie charts to help explain findings to stakeholders. These are all examples of what?
Question 3When does causation, or a cause-effect relationship, occur?
Question 4Which of the following are part of McCandless’s elements of effective data visualization? Select all that apply.
L3 Designing data visualizationsQuestion 1Which element of design can add visual form to your data and help build the structure for your visualization?
Question 2Which of the following are elements for effective visuals? Select all that apply.
The elements for effective visuals are clear meaning, sophisticated use of contrast, and refined execution. Question 3Fill in the blank: Design thinking is a process used to solve complex problems in a _ way.
Question 4While creating a data visualization for your stakeholders, you realize certain colors might make it harder for your audience to understand your data. What phase of the design process does this represent?
L4 Explore visualization considerationsQuestion 1What are the three basic visualization considerations? Select all that apply.
Question 2Directly labeling a data visualization helps viewers identify data more efficiently. Legends are often less effective because they are positioned away from the data.
Question 3In what ways can data analysts use alternative text to make their data visualizations more accessible?
Question 4You are creating a data visualization and want to ensure it is accessible. What strategies do you use to simplify the visual? Select all that apply.
Weekly challenge 1Question 1A data analyst wants to create a visualization that demonstrates how often data values fall into certain ranges. What type of data visualization should they use?
Question 2A data analyst notices that two variables in their data seem to rise and fall at the same time. They recognize that these variables are related somehow. What is this an example of?
Question 3Fill in the blank: A data analyst creates a presentation for stakeholders. They include _ visualizations because they want them to be interactive and automatically change over time.
Question 4What are the key elements of effective visualizations you should focus on when creating data visualizations? Select all that apply.
Question 5Fill in the blank: Design thinking is a process used to solve problems in a _ way.
Question 6You are in the ideate phase of the design process. What are you doing at this stage?
Question 7A data analyst wants to make their visualizations more accessible by adding text explanations directly on the visualization. What is this called?
Question 8Distinguishing elements of your data visualizations makes the content easier to see. This can help make them more accessible for audience members with visual impairments. What are some methods data analysts use to distinguish elements?
Week 2: Creating data visualizations with TableauTableau is a tool that helps data analysts create effective data visualizations. In this part of the course, you’ll learn all about Tableau and explore the importance of creativity and clarity while visualizing your data analysis findings. Learning Objectives
Answers to week 2 quiz questionsL2 Getting started with TableauQuestion 1As a business intelligence and analytics platform, Tableau enables you to do what with data? Select all that apply.
Question 2You are comparing Tableau to Looker and Google Data Studio for your company’s data visualization needs. What feature is unique to Tableau?
Question 3Fill in the blank: When using Tableau Public, click the Gallery tab to access _.
L3 Create visualizations in TableauQuestion 1A diverging color palette in Tableau displays characteristics of values using what color combination?
Question 2A data analyst creates a Tableau visualization to compare the trade (amount of goods and services exchanged) between the European Union (EU) and Australia. Which color choice could be misleading?
Question 3How could you adjust the labels to make the following visualization more effective? Select all that apply. Each country has statistics for family, health, freedom, and generosity
Weekly challenge 2Question 1Fill in the blank: When using Tableau, people can control what data they see in a visualization. This is an example of Tableau being _.
Question 2A data analyst is using the Color tool in Tableau to apply a color scheme to a data visualization. They want the visualization to be accessible for people with color vision deficiencies, so they use a color scheme with lots of contrast. What does it mean to have contrast?
Question 3What could a data analyst do with the Lasso tool in Tableau?
Question 4A data analyst is using the Pan tool in Tableau. What are they doing?
Question 5You are working with the World Happiness data in Tableau. To display the population of each country on the map, which Marks shelf tool do you use?
Question 6When working with the World Happiness data in Tableau, what could you use the Filter tool to do?
Question 7By default, all visualizations you create using Tableau Public are available to other users. What icon to you click to hide a visualization?
Question 8Fill in the blank: In Tableau, a _ palette displays two ranges of values. It uses a color to show the range where a data point is from and color intensity to show its magnitude.
Week 3: Crafting data storiesConnecting your objective with your data through insights is essential to good data storytelling. In this part of the course, you’ll learn about data-driven stories and their attributes. You’ll also gain an understanding of how to use Tableau to create dashboards and dashboard filters. Learning Objectives
Answers to week 3 quiz questionsL2 Data-driven storiesQuestion 1Data storytelling involves which of the following elements? Select all that apply.
Question 2A data analyst presents their data story to an audience. They aim to capture and hold the audience members’ interest and attention. Which data storytelling concept does this describe?
Question 3Which of the following activities would a data analyst do while spotlighting? Select all that apply.
L3 Use Tableau dashboardQuestion 1Fill in the blank: A dashboard organizes information from multiple datasets into one central location. This enables the information to be _. Select all that apply.
Question 2A data analyst is choosing their Tableau dashboard layout. They want the layout to automatically resize itself based on the dashboard size. They should use a tiled layout.
L4 Communicate data storiesQuestion 1A new challenge from a competitor, an inefficient process that needs to be improved, or a potential business opportunity could all represent which aspect of data storytelling?
Question 2Fill in the blank: When designing a presentation, a slideshow tool called _ can be used to control the color, font types and sizes, formating, and positioning of text and visuals.
Question 3A data analyst includes a visual in their presentation to represent information from a dataset. It’s important that the visual reflect the latest information, so the analyst wants it to update automatically if the original dataset changes. The analyst should copy and paste the visual into the presentation.
Weekly challenge 3Question 1Engaging your audience, creating compelling visuals, and using an interesting narrative are all part of what practice?
Question 2A data analyst wants to communicate to others about their analysis. They ensure the communication has a beginning, a middle, and an end. Then, they confirm that it clearly explains important insights from their analysis. What aspect of data storytelling does this scenario describe?
Question 3You are preparing to communicate to an audience about an analysis project. You consider the roles that your audience members play and their stake in the project. What aspect of data storytelling does this scenario describe?
Question 4When designing a dashboard, how can data analysts ensure that charts and graphs are most effective? Select all that apply.
Question 5A data analyst is creating a dashboard using Tableau. In order to layer objects over other items, which layout should they choose?
Question 6Which of the following are appropriate uses for filters in Tableau? Select all that apply.
Question 7A data analyst creates a dashboard in Tableau to share with stakeholders. They want to save stakeholders time and direct them to the most important data points. To achieve these goals, they can pre-filter the dashboard.
Question 8An effective slideshow guides your audience through your main communication points. What are some best practices to use when writing text for a slideshow? Select all that apply.
Question 9You are creating a slideshow for a client presentation. There is a pivot table in a spreadsheet that you want to include. In order for the pivot table to update whenever the spreadsheet source file changes, how should you incorporate it into your slideshow? Select all that apply.
Week 4: Developing presentations and slideshowsIn this part of the course, you’ll discover how to give an effective presentation about your data analysis. You’ll consider all aspects of your analysis when creating the presentation, as well as how to use multiple data sources in the data visualizations you share. In addition, you’ll learn how to anticipate and respond to potential limitations and questions that may arise. Learning Objectives
Answers to week 4 quiz questionsL2 Effective presentationsQuestion 1Which of the following is an example of a business task? Select all that apply.
Question 2A supervisor asks a junior data analyst to present two hypotheses regarding a data analytics project. What is the purpose of a hypothesis?
Question 3Which of the following is an example of an initial hypothesis? Select all that apply.
Question 4In the McCandless Method, the first step involves communicating to the audience where they should focus and what the graphic is about. Which step is this?
L3 Presentation skills and practicesQuestion 1Which techniques can be helpful to prevent nerves before a presentation? Select all that apply.
Question 2Which technique can make it easier to keep your body calm before a presentation?
Question 3Which practices are helpful for keeping an audience focused on your presentation? Select all that apply.
Caveats and limitations to dataQuestion 1What is the technique that data analysts use to help them anticipate the questions a stakeholder might have during a Q&A?
Question 2You present to your stakeholders, and they express concern about how your results compare to previous results. Which kind of objection are they making?
Question 3After your presentation, a stakeholder is concerned about whether your data comes from a reputable source. In what ways should you respond? Select all that apply.
L5 Listen, respond and includeQuestion 1After you finish giving a presentation, and an audience member asks your team about additional information on your topic. Your coworker is answering the question thoroughly, but you notice that the rest of your audience has tuned out. How can you re-engage your audience? Select all that apply.
Question 2You answer a question from an audience member, who then seems confused. You conclude that you didn’t understand the question. What should you have done differently to avoid the issue? Select all that apply.
Question 3Your audience has several questions after your presentation, and you may not have enough time to answer them all. How should you proceed?
Weekly challenge 4Question 1A data analyst gives a presentation about predicting upcoming investment opportunities. How does establishing a hypothesis help the audience understand their predictions?
Question 2According to the McCandless Method, what is the most effective way to first present a data visualization to an audience?
Question 3An analyst introduces a graph to their audience to explain an analysis they performed. Which strategy would allow the audience to absorb the data visualizations? Select all that apply.
Question 4You are preparing for a presentation and want to make sure your nerves don’t distract you from your presentation. Which practices can help you stay focused on an audience? Select all that apply.
Question 5You run a colleague test on your presentation before getting in front of an audience. Your coworker asks a question about a section of your analysis, but addressing their concern would mean adding information you didn’t plan to include. How should you proceed with building your presentation?
Question 6Your stakeholders are concerned about the source of your data. They are unfamiliar with the organization that ran the analyses you referenced in your presentation. Which kind of objection are they making?
Question 7A stakeholder objects to the steps of your analysis. What are some appropriate ways to respond to this objection? Select all that apply.
Question 8You are presenting to a large audience and want to keep everyone engaged during your Q&A. What can you do to ensure your audience doesn’t grow disinterested despite its size?
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