Histogram and density plots in R Programming - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a histogram of the variable 'x' using ggplot2.

R Programming

library(ggplot2)
data <- data.frame(x = rnorm(100))
ggplot(data, aes(x = x)) + geom_[1]()

Drag options to blanks, or click blank then click option'

Ahist

Bpoint

Chistogram

Dbar

Attempts:

3 left

💡 Hint

Common Mistakes

Using geom_bar() instead of geom_histogram()

Using geom_point() which creates scatter plots

The correct function to create a histogram in ggplot2 is geom_histogram().

2fill in blank

medium

Complete the code to add a density plot layer on top of the histogram.

R Programming

ggplot(data, aes(x = x)) + geom_histogram(binwidth = 0.5, fill = 'blue', alpha = 0.5) + geom_[1](color = 'red')

Drag options to blanks, or click blank then click option'

Adensity

Bhist

Cline

Dsmooth

Attempts:

3 left

💡 Hint

Common Mistakes

Using geom_hist() again instead of geom_density()

Using geom_line() which requires y aesthetic

The function geom_density() adds a density plot layer.

3fill in blank

hard

Fix the error in the code to correctly plot a histogram with density on y-axis.

R Programming

ggplot(data, aes(x = x, y = ..[1]..)) + geom_histogram(binwidth = 0.3)

Drag options to blanks, or click blank then click option'

Avalue

Bdensity

Cfrequency

Dcount

Attempts:

3 left

💡 Hint

Common Mistakes

Using y = ..count.. which shows counts instead of density

Using y = ..value.. which is invalid

Using y = ..density.. scales the histogram to show density instead of counts.

4fill in blank

hard

Fill both blanks to create a histogram with density overlay and set transparency.

R Programming

ggplot(data, aes(x = x)) + geom_histogram(binwidth = 0.4, fill = 'green', alpha = [1]) + geom_[2](color = 'black', size = 1)

Drag options to blanks, or click blank then click option'

A0.3

B0.7

Cdensity

Dline

Attempts:

3 left

💡 Hint

Common Mistakes

Using alpha greater than 1 or less than 0

Using geom_line() instead of geom_density()

Alpha controls transparency; 0.7 is a good choice. geom_density() adds the density line.

5fill in blank

hard

Fill all three blanks to create a histogram with density overlay, set binwidth, and add title.

R Programming

ggplot(data, aes(x = x)) + geom_histogram(binwidth = [1], fill = 'purple', alpha = 0.6) + geom_density(color = [2], size = 1) + ggtitle([3])

Drag options to blanks, or click blank then click option'

A0.2

B'red'

C"Histogram with Density"

D0.5

Attempts:

3 left

💡 Hint

Common Mistakes

Not quoting the title string

Using invalid binwidth values

Binwidth 0.5 is reasonable. Color 'red' for density line. Title must be a string in quotes.

Practice

1. What is the main difference between a histogram and a density plot in R?

easy

A. Histogram shows exact values; density plot shows counts only.

B. Histogram uses bars; density plot uses a smooth curve.

C. Histogram is for categorical data; density plot is for numeric data.

D. Histogram requires ggplot2; density plot does not.

Solution

1. Step 1: Understand histogram representation

   A histogram displays data grouped into bins using bars to show frequency counts.

2. Step 2: Understand density plot representation

   A density plot shows a smooth curve estimating the data distribution, not bars.

3. Final Answer:

   Histogram uses bars; density plot uses a smooth curve. -> Option B

4. Quick Check:

   Histogram = bars, Density plot = smooth curve [OK]

Hint: Bars mean histogram; smooth curve means density plot [OK]

Common Mistakes:

• Thinking histogram shows exact values instead of grouped counts
• Confusing density plot with bar charts
• Assuming histograms only work with categorical data

2. Which of the following is the correct R code to create a histogram of the numeric vector data?

easy

A. hist(data)

B. plot.histogram(data)

C. histogram(data)

D. density(data)

Solution

1. Step 1: Recall the base R function for histograms

   The correct function to create a histogram in base R is hist().

2. Step 2: Check the options

   Only hist(data) is valid syntax; others are either incorrect function names or for density plots.

3. Final Answer:

   hist(data) -> Option A

4. Quick Check:

   hist() creates histograms in R [OK]

Hint: Use hist() for histograms in base R [OK]

Common Mistakes:

• Using non-existent function histogram()
• Confusing density() with hist()
• Trying plot.histogram() which is invalid

3. What will be the output of the following R code?

set.seed(1)
data <- rnorm(100)
hist(data, breaks=5, col='blue')

medium

A. An error because breaks cannot be numeric

B. A density plot with 5 blue lines

C. A histogram with 5 blue bars showing data distribution

D. A scatter plot of 100 points

Solution

1. Step 1: Understand hist() with breaks parameter

   The breaks=5 argument divides data into 5 bins for the histogram.

2. Step 2: Check color and plot type

   The col='blue' colors the bars blue; hist() creates a bar plot, not a density or scatter plot.

3. Final Answer:

   A histogram with 5 blue bars showing data distribution -> Option C

4. Quick Check:

   hist() + breaks=5 + col='blue' = blue bars histogram [OK]

Hint: breaks sets bar count; col sets bar color [OK]

Common Mistakes:

• Thinking breaks=5 creates density plot
• Assuming breaks cannot be numeric
• Confusing hist() with scatter plot

4. Identify the error in this R code for plotting a density plot:

data <- rnorm(50)
density(data, col='red')

medium

A. density() does not accept a col argument directly

B. rnorm() cannot generate 50 values

C. Missing parentheses after density

D. data must be a data frame, not a vector

Solution

1. Step 1: Check density() function usage

   The density() function returns density data but does not plot directly or accept col.

2. Step 2: Correct plotting method

   To plot with color, use plot(density(data), col='red') instead.

3. Final Answer:

   density() does not accept a col argument directly -> Option A

4. Quick Check:

   density() returns data; plot() colors it [OK]

Hint: Use plot(density()) to color density plots [OK]

Common Mistakes:

• Passing col directly to density()
• Thinking density() plots automatically
• Assuming rnorm() can't generate 50 values

5. You want to compare the distribution of two numeric vectors x and y in R using a single plot. Which code correctly overlays their density plots with different colors?

hard

A. plot(density(x, col='blue'), density(y, col='red'))

B. hist(x, col='blue'); hist(y, col='red')

C. density(x, col='blue'); density(y, col='red')

D. plot(density(x), col='blue'); lines(density(y), col='red')

Solution

1. Step 1: Plot first density with plot()

   Use plot(density(x), col='blue') to draw the first density curve in blue.

2. Step 2: Add second density with lines()

   Use lines(density(y), col='red') to overlay the second density curve in red.

3. Final Answer:

   plot(density(x), col='blue'); lines(density(y), col='red') -> Option D

4. Quick Check:

   plot() then lines() overlays densities with colors [OK]

Hint: plot() first density, lines() add second [OK]

Common Mistakes:

• Using hist() which creates separate plots
• Passing col to density() instead of plot() or lines()
• Trying to plot both densities in one plot() call