Module 1 challenge :Data Analysis with R Programming (Google Data Analytics Professional Certificate) Answers 2025

Question 1

A data analyst wants a tool to communicate instructions a computer can run.

✅ Programming language
❌ Algebra
❌ Statistics
❌ Analytics

Explanation:
A programming language (like R, Python, SQL) is designed to give computers precise, executable instructions for data analysis, automation, and computation.

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Question 2

Using a programming language can help you with which aspects of data analysis?

✅ Clean your data
✅ Transform your data
✅ Visualize your data
❌ Ask the right questions about your data

Explanation:
Languages like R and Python help analysts clean, transform, and visualize data efficiently.
But asking the right questions is part of analytical thinking, not coding.

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Question 3

A data analyst wants to use a programming language they can modify.

✅ Open-source
❌ Community-oriented
❌ Console-based
❌ Data-centric

Explanation:
Open-source languages (like R and Python) can be freely modified and shared — users can improve, extend, and customize them.

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Question 4

Why do many data analysts choose R?

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

Explanation:
R is open-source, focused on data analysis and visualization, and can handle large datasets efficiently — making it ideal for analytics and reporting.

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Question 5

Benefits of using R for data analysis:

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

Explanation:
R is specialized for statistics, analysis, and visualization, not general-purpose development.
It’s known for data manipulation and high-quality visuals (via ggplot2, Shiny, etc.).

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Question 6

Which statements about RStudio IDE are correct?

✅ RStudio includes a built-in console.
✅ RStudio panes are customizable.
❌ RStudio is closed-source.
❌ RStudio only works on Windows.

Explanation:
RStudio is open-source, works on Windows, macOS, and Linux, includes a console, and lets users customize panes (scripts, plots, environment, etc.).

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Question 7

Where should R code be written if it should go away after closing RStudio?

✅ R console
❌ Plots tab
❌ Environment tab
❌ Source editor

Explanation:
Code written in the R console runs immediately and is not saved after you close the session.
Use the Source editor if you want code to persist.

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Question 8

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

✅ Environment pane
❌ Plots tab
❌ Source editor pane
❌ R console pane

Explanation:
The Environment pane shows all objects, data frames, and variables loaded into memory — you can view, remove, or inspect them.

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🧾 Summary Table

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