Coursera Google Data Analytics Professional Share Data Through the Art of Visualization (Week 1) Quiz Answer-Visualizing data.

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1.Visualizing data.

Question 1

A 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?

• Histogram
• Scatter plot
• Line graph
• Correlation chart

To demonstrate how often data values fall into certain ranges, the data analyst should use a histogram.

Question 2

A 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?

• Causation
• Correlation
• Tabulation
• Visualization

When a data analyst notices that two variables rise and fall at the same time, this is an example of correlation. Correlation is the measure of the degree to which two variables change in relationship to each other.

 

Question 3

Fill 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.

• dynamic
• aesthetic
• geometric
• static

They include dynamic visualizations. Dynamic visualizations are interactive and can automatically change over time.

Question 4

What are the key elements of effective visualizations you should focus on when creating data visualizations? Select all that apply.

• Sophisticated use of contrast
• Visual form
• Clear meaning
• Refined execution

The elements for effective visualization are clear meaning, sophisticated use of contrast, and refined execution.

 

Question 5

Fill in the blank: Design thinking is a process used to solve problems in a _____ way.

• critical
• user-centric
• design-centric
• analytical

Design thinking is a process used to solve complex problems in a user-centric way.

Question 6

You are in the ideate phase of the design process. What are you doing at this stage?

• Sharing data visualizations with a test audience
• Generating visualization ideas
• Creating data visualizations
• Making changes to their data visualization

There are five phases of the design process: empathize, define, ideate, prototype, and test. The ideate phase is when you start to generate your data visualization ideas.

 

Question 7

A data analyst wants to make their visualizations more accessible by adding text explanations directly on the visualization. What is this called?

• Subtitling
• Simplifying
• Labeling
• Distinguishing

This is labeling. Labeling data directly instead of relying on legends can make data visualizations more accessible.

Question 8

Distinguishing 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?

• Add a legend
• Separate the foreground and background
• Use contrasting colors and shapes
• Ensure all elements are highlighted equally

Data analysts distinguish elements of data visualizations by separating the foreground and background and using contrasting colors and shapes.

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