Week 1: Programming and data analytics

1. A data analyst uses words and symbols to give instructions to a computer. What are the words and symbols known as?

  • Coded language
  • Function language
  • Programming languages
  • Syntax languages

2. Many data analysts prefer to use a programming language for which of the following reasons? Select all that apply.

  • To save time
  • To clarify the steps of an analysis
  • To easily reproduce and share an analysis
  • To choose a topic for analysis

3. Fill in the blank: _____ code is freely available and may be modified and shared by the people who use it.

  • Open-ended
  • Open-source
  • Open-access
  • Open-syntax

4. Which of the following are benefits of using R for data analysis? Select all that apply.

  • Create high-quality data visualizations
  • Define a problem and ask the right questions
  • Process lots of data
  • Reproduce and share an analysis

5. Fill in the blank: A data analyst wants to quickly create visualizations and then share them with a teammate. They can use _____ for the analysis.

  • the R programming language
  • a dashboard
  • structured query language
  • a database

6. RStudio’s integrated development environment includes which of the following? Select all that apply.

  • A console for executing commands
  • An area to manage loaded data
  • A viewer for playing videos
  • An editor for writing code

7. Fill in the blank: When you execute code in the source editor, the code automatically also appears in the _____.

  • R console
  • plots tab
  • environment pane
  • files tab

8. A data analyst is working with spreadsheet data. The analyst imports the data from the spreadsheet into RStudio. Where in RStudio can the analyst find the imported data?

  • Source editor pane
  • Environment pane
  • R console pane
  • Plots tab

9. Fill in the blank: _____ are the words and symbols you use to write instructions for computers.

  • Code languages
  • Programming languages
  • Syntax languages
  • Variable languages

10. A data analyst wants to use a programming language that they can modify. What type of programming language should they use?

  • Console-based
  • Data-centric
  • Community-oriented
  • Open-source

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

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

21. What is the term for programming code that is freely available and may be modified and shared by the people who use it?

  • Open-source
  • Open-ended
  • Data-centric
  • Open-data

22. For what reasons do many data analysts choose to use R? Select all that apply.

  • R can quickly process lots of data.
  • R is a data-centric programming language.
  • R can create high quality visualizations.
  • R is a closed source programming language.

23. What is a benefit of using the R programming language for data analysis? Select all that apply.

  • It is the most popular machine-learning language.
  • It is a general-purpose programming language.
  • It can create world-class visualizations.
  • It can work with large amounts of data

24. RStudio’s integrated development environment lets you perform which of the following actions? Select all that apply.

  • Install R packages
  • Import data from spreadsheets
  • Create data visualizations
  • Stream online videos

25. Fill in the blank: In RStudio, the _____ is where you can find all the data you currently have loaded, organize it, and save it.

  • source editor pane
  • environment pane
  • R console pane
  • plots pane

26. Which of the following are benefits of open-source code? Select all that apply.

  • Anyone can pay a fee for access to the code.
  • Anyone can use the code for free.
  • Anyone can fix bugs in the code.
  • Anyone can create an add-on package for the code.

27. A data analyst is searching for an open-source tool that will allow them to work with very large amounts of data. What tool is the best option?

  • Spreadsheet
  • JSON
  • R
  • Tableau

28. In RStudio, where can you find and manage all the data you currently have loaded?

  • R console pane
  • Plots tab
  • Source editor pane
  • Environment pane

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

  • Clarify the steps of the analysis
  • Easily reproduce and share the analysis
  • Automatically choose a topic for analysis
  • Efficiently save time

30. What attribute of the R programming language makes it an open-source programming language?

  • The code is designed to be data-centric.
  • The code is open to processing large amounts of data.
  • The code is distributed by a company named “Open-Source.”
  • The code can be modified and shared by anyone who uses it.

31. In which two parts of RStudio can you execute code? Select all that apply.

  • The environment pane
  • The source editor pane
  • The R console pane
  • The plots pane

32. How do data analysts refer to the words and symbols they use to write instructions for computers?

  • Programming languages
  • Syntax languages
  • Code languages
  • Variable languages

33. A data analyst wants to write R code in RStudio that will go away after they close their current session. Where should they write their code?

  • Environment tab
  • Source editor
  • Plots tab
  • R console

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

  • It does not require data cleaning
  • It is faster to clean data.
  • It is easy to share code.
  • It does not require specific syntax.

35. In RStudio, where can you find a list of all of the R commands you have run in your current sessions?

  • Help tab
  • Files tab
  • Source editor
  • History tab

36. What is a type of application that brings together all the tools a data analyst may want to use in a single place?

  • Spreadsheet
  • Integrated development environment
  • Database
  • Dashboard

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