Week 1 – Effective questions – Shuffle Q/A 3

31. What is the defining characteristic of measurable questions?

  • They are questions that have numbers in them.
  • Their answers are numbers that can be interpreted qualitatively.
  • They are questions that use numbers as categories.
  • Their answers are numbers that can be interpreted mathematically.

32. Fill in the blank: “How many people filled out the survey?” is an example of a question that is _____ in the context of data analysis.

  • categorical
  • symbolic
  • measureable
  • qualitative

33. Fill in the blank: In the _____ step of the data analysis process, an analyst would create visualizations to summarize their results.

  • process
  • share
  • prepare
  • act

34. A community college wishes to share information about their new career technical degrees. Who are likely examples of their target audience? Select all that apply.

  • Students newly enrolled at a state university
  • People who are happy with their current jobs
  • People looking for a career change
  • Students who just graduated high school

35. A restaurant is considering offering a delivery option for its customers. They use data to forecast the demand for this service. This is an example of which problem type?

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

36. Fill in the blank: The question, “How could we improve our website to simplify the returns process for our online customers?” is _____-oriented.

  • action
  • passive
  • data
  • bias

37. Why is reaching your target audience important in data analysis?

  • It brings awareness of your products to potential customers.
  • It makes your products easier to use for your customers.
  • It improves customer service for those currently using your products.
  • It increases the effectiveness of your services for customers.

38. Making predictions is one of the six data analytics problem types. It deals with using data to inform decisions about how things might be in the future. Select the scenario that’s an example of making predictions.

  • A data analyst at a gas company uses historical data to analyze a fluctuation in gas usage.
  • A data analyst at a school system uses data to make a connection between home sales and new student enrollment.
  • A data analyst at a shoe retailer uses data to inform the marketing plan for an upcoming summer sale.
  • A data analyst at a technology company uses data to identify a unique drop in social media engagement.

Shuffle Q/A 4

39. Fill in the blank: Questions that make assumptions or suggest that a given answer is correct are examples of _____ questions.

  • unbiased
  • fair
  • wrong
  • unfair

40. In structured thinking, why would a data analyst organize the available information?

  • To recognize the current problem or situation
  • To consult with subject matter experts
  • To ask SMART questions
  • To summarize results using data visualizations

Devendra Kumar

Project Management Apprentice at Google

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