Welcome to your ultimate guide for Exploratory Data Analysis quiz answers! Whether you’re tackling practice quizzes to solidify your skills or preparing for graded quizzes to assess your understanding, this guide has you covered.
Spanning all course modules, this resource will help you master key exploratory data analysis techniques, including data visualization, summary statistics, and identifying patterns or outliers in your data.
Exploratory Data Analysis Quiz Answers for All Modules
Table of Contents
Exploratory Data Analysis Week 01 Quiz Answers
Q1. Which of the following is a principle of analytic graphics?
Explanation: Analytic graphics principles help ensure that data visualizations are effective and easy to understand. The right use of color, simplicity, and appropriate types of plots are key factors.
Answer: Make judicious use of color in your scatterplots
Q2. What is the role of exploratory graphs in data analysis?
Explanation: Exploratory graphs are tools used in the initial stages of analysis to help understand data patterns and relationships, often guiding further analysis.
Answer: The goal is for personal understanding.
Q3. Which of the following is true about the base plotting system?
Explanation: The base plotting system in R is straightforward for creating simple plots but often requires separate functions for customization and annotation.
Answer: Plots are created and annotated with separate functions.
Q4. Which of the following is an example of a valid graphics device in R?
Explanation: A graphics device in R is where graphical outputs are rendered. The screen is a common example of a graphics device.
Answer: The computer screen
Q5. Which of the following is an example of a vector graphics device in R?
Explanation: Vector graphics devices create images that scale well without losing resolution, ideal for publication-quality graphics.
Answer: Postscript
Q6. Bitmapped file formats can be most useful for
Explanation: Bitmapped formats are pixel-based and are suitable for detailed visualizations like scatterplots with many points.
Answer: Scatterplots with many many points
Q7. Which of the following functions is typically used to add elements to a plot in the base graphics system?
Explanation: The points() function is commonly used to add additional points to an existing plot.
Answer: points()
Q8. Which function opens the screen graphics device on Windows?
Explanation: The windows() function opens a graphics device on Windows for visualizing plots.
Answer: windows()
Q9. What does the ‘pch’ option to par() control?
Explanation: The ‘pch’ option controls the plotting symbol used in scatterplots to represent data points.
Answer: the plotting symbol/character in the base graphics system
Q10. If I want to save a plot to a PDF file, which of the following is a correct way of doing that?
Explanation: To save a plot as a PDF in R, the device should be opened with pdf() and closed with dev.off() to finalize the plot.
Answer: Construct the plot on the screen device and then copy it to a PDF file with dev.copy2pdf()
Exploratory Data Analysis Week 02 Quiz Answers
Q1. Under the lattice graphics system, what do the primary plotting functions like xyplot() and bwplot() return?
Explanation: In the lattice system, functions like xyplot() and bwplot() return objects that represent a plot but are not immediately displayed. These objects are part of the “trellis” class, which is used to manage multi-panel plots.
Answer: an object of class “trellis”
Q2. What is produced by the following code?
rCopyEditlibrary(nlme)
library(lattice)
xyplot(weight ~ Time | Diet, BodyWeight)
Explanation: This code produces a lattice plot showing the relationship between weight and time for each diet. Since the xyplot() function is conditioned on the variable Diet, it generates separate panels for each diet.
Answer: A set of 3 panels showing the relationship between weight and time for each diet.
Q3. Which of the following functions can be used to annotate the panels in a multi-panel lattice plot?
Explanation: In the lattice graphics system, functions like text() and points() can be used to add annotations to the plot panels. points() can add points, and text() can add text annotations.
Answer: points()
Q4. The following code does NOT result in a plot appearing on the screen device.
rCopyEditlibrary(lattice)
library(datasets)
data(airquality)
p <- xyplot(Ozone ~ Wind | factor(Month), data = airquality)
Explanation: The xyplot() function creates the plot and stores it in the variable p, but it does not automatically display it. To display the plot, you need to explicitly print the object p.
Answer: The object ‘p’ has not yet been printed with the appropriate print method.
Q5. In the lattice system, which of the following functions can be used to finely control the appearance of all lattice plots?
Explanation: trellis.par.set() is used to customize the overall appearance (themes, colors, etc.) of all lattice plots.
Answer: trellis.par.set()
Q6. What is ggplot2 an implementation of?
Explanation: ggplot2 is an implementation of the Grammar of Graphics, a framework for creating consistent and flexible data visualizations.
Answer: the Grammar of Graphics developed by Leland Wilkinson
Q7. Load the `airquality’ dataset from the datasets package in R.
rCopyEditlibrary(datasets)
data(airquality)
I am interested in examining how the relationship between ozone and wind speed varies across each month. What would be the appropriate code to visualize that using ggplot2?
Explanation: The qplot() function is used to quickly create plots. The facets argument is used to create separate panels for each month.
Answer: qplot(Wind, Ozone, data = airquality, facets = . ~ Month)
Q8. What is a geom in the ggplot2 system?
Explanation: In ggplot2, a “geom” represents the geometric object used to display data, such as points, lines, bars, etc.
Answer: a plotting object like point, line, or other shape
Q9. When I run the following code I get an error:
rCopyEditlibrary(ggplot2)
library(ggplot2movies)
g <- ggplot(movies, aes(votes, rating))
print(g)
Explanation: The issue is that ggplot() does not know what type of plot to draw unless you specify a geom layer (e.g., geom_point() for a scatterplot).
Answer: ggplot does not yet know what type of layer to add to the plot.
Q10. The following code creates a scatterplot of ‘votes’ and ‘rating’ from the movies dataset in the ggplot2 package. After loading the ggplot2 package with the library() function, I can run:
rCopyEditqplot(votes, rating, data = movies)
How can I modify the code above to add a smoother to the scatterplot?
Explanation: To add a smoother (e.g., LOESS), you use geom_smooth() in the qplot() function.
Answer: qplot(votes, rating, data = movies) + geom_smooth()
Frequently Asked Questions (FAQ)
Are the Exploratory Data Analysis quiz answers accurate?
Yes, these answers are carefully reviewed to ensure they align with the latest course material and best practices in exploratory data analysis.
Can I use these answers for both practice and graded quizzes?
Absolutely! These answers are designed for both practice quizzes and graded assessments, ensuring you’re fully prepared for all evaluations.
Does this guide cover all modules of the course?
Yes, this guide provides answers for every module, ensuring complete coverage of the entire course content.
Will this guide help me improve my data exploration and analysis skills?
Yes, in addition to providing quiz answers, this guide reinforces key concepts such as visualizing data distributions, calculating summary statistics, detecting outliers, and using tools like histograms, scatter plots, and box plots for analysis.
Conclusion
We hope this guide to Exploratory Data Analysis Quiz Answers helps you master the art of data exploration and succeed in your course. Bookmark this page for quick access and share it with your peers. Ready to uncover hidden insights in your data and ace your quizzes? Let’s get started!
Sources: Exploratory Data Analysis
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