7/2/25, 9:04 PM Midterm Exam 1 - Open Book Section (R) - Part 2
Midterm Exam 1 - Open Book Section (R)
- Part 2
Instructions
The R Markdown/Jupyter Notebook file includes the questions, the empty code chunk sections for your code, and
the text blocks for your responses. Answer the questions below by completing the R Markdown/Jupyter Notebook
file. You may make slight adjustments to get the file to knit/convert but otherwise keep the formatting the same.
Once you’ve finished answering the questions, submit your responses in a single knitted file as HTML only.
Next Steps:
1. Save the .Rmd/.ipnyb file in your R working directory - the same directory where you will download the
“diamonds.csv” data file into. Having both files in the same directory will help in reading the “diamonds.csv”
file.
2. Read the question and create the R code necessary within the code chunk section immediately below each
question. Knitting this file will generate the output and insert it into the section below the code chunk.
3. Type your answer to the questions in the text block provided immediately after the response prompt.
4. Once you’ve finished answering all questions, knit this file and submit the knitted file as HTML on Canvas.
* Make sure to start submission of the exam at least 10 minutes before the end of the exam
time. It is your responsibility to keep track of your time and submit before the time limi
t.
* If you are unable to knit your file as HTML for whatever reason, you may upload your Rm
d/ipynb/PDF/Word file instead. However, you will be penalized 10%.
* If you are unable to upload your exam file for whatever reason, you may IMMEDIATELY atta
ch the file to the exam page as a comment via Grades-> Midterm Exam 1 - Open Book Section
(R) - Part 2 -> Comment box.
* Note that you will be penalized 10% (or more) if the submission is made within 5 minutes
after the exam time has expired and a higher penalty if more than 5 minutes. Furthermore,
you will receive zero points if the submission is made after 15 minutes of the exam time e
xpiring. We will not allow later submissions or re-taking of the exam.
* If you upload your file after the exam closes, let the instructors know via a private Pi
azza post. Please DON'T attach the exam file via a private Piazza post to the instructors
since you could compromise the exam process. Any submission received via Piazza will not b
e considered.
Mock Example Question
This will be the exam question - each question is already copied from Canvas and inserted into individual text
blocks below. You do not need to copy/paste the questions from the online Canvas exam.
file:///C:/Users/shani/Downloads/SPRING2024_Midterm_1_Part_2_Solutions_R.html 1/21
,7/2/25, 9:04 PM Midterm Exam 1 - Open Book Section (R) - Part 2
# Example code chunk area. Enter your code below the comment
Mock Response to Example Question: This is the section where you type your written answers to the question.
Ready? Let’s begin.
Background
In this exam, you will be considering various attributes of diamonds to predict their price.
A data frame with 53940 rows and 10 variables:
1. price: price in US dollars (\$326–\$18,823) (response variable)
2. carat: weight of the diamond (0.2–5.01)
3. cut: quality of the cut (Fair, Good, Very Good, Premium, Ideal)
4. color: diamond color, from D to J
5. clarity: a measurement of how clear the diamond is (I1 (worst), SI2, SI1, VS2, VS1, VVS2, VVS1, IF (best))
6. x: length in mm (0–10.74)
7. y: width in mm (0–58.9)
8. z: depth in mm (0–31.8)
9. depth: total depth percentage = z/mean(x, y) = (2 ∗ z)/(x + y) (in percentage) (43-79)
10. table: width of top of diamond relative to widest point in percentage (43–95)
#read the csv file
diamonds = read.csv("diamonds.csv",header=TRUE)
diamonds$cut=as.factor(diamonds$cut)
diamonds$color=as.factor(diamonds$color)
diamonds$clarity=as.factor(diamonds$clarity)
head(diamonds)
## carat cut color clarity depth table x y z price
## 1 0.23 Ideal E SI2 61.5 55 3.95 3.98 2.43 326
## 2 0.21 Premium E SI1 59.8 61 3.89 3.84 2.31 326
## 3 0.23 Good E VS1 56.9 65 4.05 4.07 2.31 327
## 4 0.29 Premium I VS2 62.4 58 4.20 4.23 2.63 334
## 5 0.31 Good J SI2 63.3 58 4.34 4.35 2.75 335
## 6 0.24 Very Good J VVS2 62.8 57 3.94 3.96 2.48 336
NOTE: Use the dataset “diamonds” for all the questions.
Question 1: EXPLORATORY DATA ANALYSIS (13
points)
1a) (3 points) Create a boxplot of the predicting variable “color” versus the response variable “price”.
Explain the relationship between the two variables based on the boxpolot.
#Code to create plot
library(ggplot2)
file:///C:/Users/shani/Downloads/SPRING2024_Midterm_1_Part_2_Solutions_R.html 2/21
, 7/2/25, 9:04 PM Midterm Exam 1 - Open Book Section (R) - Part 2
##
## Attaching package: 'ggplot2'
## The following object is masked _by_ '.GlobalEnv':
##
## diamonds
ggplot(diamonds, aes(x=color, y=price, color=color)) +
geom_boxplot() +
ggtitle("Box Plot of region vs charges")
Answer to Question 1a: The price range for the diamonds with the colors from D to J increases in general . All the
colors are overlapping, therefore, it is difficult to state that the prices are statistically significantly different among all
the pairs of the colors without further analysis.
1b) (3 points) Perform an ANOVA F-test on the means of the colors of the diamonds.
i) State the alternative hypothesis.
ii) Using an α-level of 0.01, do we reject the null hypothesis that the means of all the colors are equal?
Explain your conclusion.
file:///C:/Users/shani/Downloads/SPRING2024_Midterm_1_Part_2_Solutions_R.html 3/21
Midterm Exam 1 - Open Book Section (R)
- Part 2
Instructions
The R Markdown/Jupyter Notebook file includes the questions, the empty code chunk sections for your code, and
the text blocks for your responses. Answer the questions below by completing the R Markdown/Jupyter Notebook
file. You may make slight adjustments to get the file to knit/convert but otherwise keep the formatting the same.
Once you’ve finished answering the questions, submit your responses in a single knitted file as HTML only.
Next Steps:
1. Save the .Rmd/.ipnyb file in your R working directory - the same directory where you will download the
“diamonds.csv” data file into. Having both files in the same directory will help in reading the “diamonds.csv”
file.
2. Read the question and create the R code necessary within the code chunk section immediately below each
question. Knitting this file will generate the output and insert it into the section below the code chunk.
3. Type your answer to the questions in the text block provided immediately after the response prompt.
4. Once you’ve finished answering all questions, knit this file and submit the knitted file as HTML on Canvas.
* Make sure to start submission of the exam at least 10 minutes before the end of the exam
time. It is your responsibility to keep track of your time and submit before the time limi
t.
* If you are unable to knit your file as HTML for whatever reason, you may upload your Rm
d/ipynb/PDF/Word file instead. However, you will be penalized 10%.
* If you are unable to upload your exam file for whatever reason, you may IMMEDIATELY atta
ch the file to the exam page as a comment via Grades-> Midterm Exam 1 - Open Book Section
(R) - Part 2 -> Comment box.
* Note that you will be penalized 10% (or more) if the submission is made within 5 minutes
after the exam time has expired and a higher penalty if more than 5 minutes. Furthermore,
you will receive zero points if the submission is made after 15 minutes of the exam time e
xpiring. We will not allow later submissions or re-taking of the exam.
* If you upload your file after the exam closes, let the instructors know via a private Pi
azza post. Please DON'T attach the exam file via a private Piazza post to the instructors
since you could compromise the exam process. Any submission received via Piazza will not b
e considered.
Mock Example Question
This will be the exam question - each question is already copied from Canvas and inserted into individual text
blocks below. You do not need to copy/paste the questions from the online Canvas exam.
file:///C:/Users/shani/Downloads/SPRING2024_Midterm_1_Part_2_Solutions_R.html 1/21
,7/2/25, 9:04 PM Midterm Exam 1 - Open Book Section (R) - Part 2
# Example code chunk area. Enter your code below the comment
Mock Response to Example Question: This is the section where you type your written answers to the question.
Ready? Let’s begin.
Background
In this exam, you will be considering various attributes of diamonds to predict their price.
A data frame with 53940 rows and 10 variables:
1. price: price in US dollars (\$326–\$18,823) (response variable)
2. carat: weight of the diamond (0.2–5.01)
3. cut: quality of the cut (Fair, Good, Very Good, Premium, Ideal)
4. color: diamond color, from D to J
5. clarity: a measurement of how clear the diamond is (I1 (worst), SI2, SI1, VS2, VS1, VVS2, VVS1, IF (best))
6. x: length in mm (0–10.74)
7. y: width in mm (0–58.9)
8. z: depth in mm (0–31.8)
9. depth: total depth percentage = z/mean(x, y) = (2 ∗ z)/(x + y) (in percentage) (43-79)
10. table: width of top of diamond relative to widest point in percentage (43–95)
#read the csv file
diamonds = read.csv("diamonds.csv",header=TRUE)
diamonds$cut=as.factor(diamonds$cut)
diamonds$color=as.factor(diamonds$color)
diamonds$clarity=as.factor(diamonds$clarity)
head(diamonds)
## carat cut color clarity depth table x y z price
## 1 0.23 Ideal E SI2 61.5 55 3.95 3.98 2.43 326
## 2 0.21 Premium E SI1 59.8 61 3.89 3.84 2.31 326
## 3 0.23 Good E VS1 56.9 65 4.05 4.07 2.31 327
## 4 0.29 Premium I VS2 62.4 58 4.20 4.23 2.63 334
## 5 0.31 Good J SI2 63.3 58 4.34 4.35 2.75 335
## 6 0.24 Very Good J VVS2 62.8 57 3.94 3.96 2.48 336
NOTE: Use the dataset “diamonds” for all the questions.
Question 1: EXPLORATORY DATA ANALYSIS (13
points)
1a) (3 points) Create a boxplot of the predicting variable “color” versus the response variable “price”.
Explain the relationship between the two variables based on the boxpolot.
#Code to create plot
library(ggplot2)
file:///C:/Users/shani/Downloads/SPRING2024_Midterm_1_Part_2_Solutions_R.html 2/21
, 7/2/25, 9:04 PM Midterm Exam 1 - Open Book Section (R) - Part 2
##
## Attaching package: 'ggplot2'
## The following object is masked _by_ '.GlobalEnv':
##
## diamonds
ggplot(diamonds, aes(x=color, y=price, color=color)) +
geom_boxplot() +
ggtitle("Box Plot of region vs charges")
Answer to Question 1a: The price range for the diamonds with the colors from D to J increases in general . All the
colors are overlapping, therefore, it is difficult to state that the prices are statistically significantly different among all
the pairs of the colors without further analysis.
1b) (3 points) Perform an ANOVA F-test on the means of the colors of the diamonds.
i) State the alternative hypothesis.
ii) Using an α-level of 0.01, do we reject the null hypothesis that the means of all the colors are equal?
Explain your conclusion.
file:///C:/Users/shani/Downloads/SPRING2024_Midterm_1_Part_2_Solutions_R.html 3/21
