Week 1 – Programming and data analytics – Shuffle Q/A 1

11. A data analyst needs to quickly create a series of scatterplots to visualize a very large dataset. What should they use for the analysis?

  • A dashboard
  • The R programming language
  • A slide presentation
  • Structured query language

12. What type of software is RStudio?

  • Integrated development environment
  • Programming language
  • Syntax
  • Pane

13. A data analyst wants to write R code where they can access it again after they close their current session in RStudio. Where should they write their code?

  • R console
  • Files tab
  • History tab
  • Source editor

14. What are the benefits of using a programming language for data analysis? Select all that apply.

  • They store steps of your analysis for future use.
  • They have no specific syntax.
  • They save time cleaning data.
  • It does not require data cleaning

15. Which of the following statements about the R programming language are correct? Select all that apply.

  • It can create world-class visualizations
  • It makes analysts spend more time cleaning data and less time analyzing
  • It can process large amounts of data
  • It relies on spreadsheet interfaces to clean and manipulate data

16. A data analyst is searching for a tool that gives them the most power to customize the visualizations they use in their analysis. What tool should they use?

  • The R Programming language
  • Tableau
  • Spreadsheets
  • SQL

17. Which of the following statements about RStudio’s integrated development environment are correct? Select all that apply.

  • R studio is unable to produce visualizations.
  • R studio is built specifically for working with R.
  • The layout of panes in R studio is fixed.
  • R studio helps with file management.

18. R users share custom solutions they have developed for data problems. Where can you find this information in RStudio?

  • Packages tab
  • History tab
  • Environment tab
  • R console

Shuffle Q/A 2

19. What tool gives data analysts the highest level of control over their data analysis?

  • Spreadsheet
  • SQL
  • Tableau
  • Programming language

20. Using a programming language can help you with which aspects of data analysis? Select all that apply.

  • Visualize your data
  • Ask the right questions about your data
  • Transform your data
  • Clean your data

Devendra Kumar

Project Management Apprentice at Google

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