Introduction to R Programming for Data Science Quiz Answer

Introduction to R Programming for Data Science Week 01 Quiz Answers

Q1. R can perform several forms of statistical computation. What is an example of hypothesis testing?

• Inferring an unknown mean value of a population from its samples.
• Compute and visualize a correlation matrix among four different variables to see if they are correlated.
• Obtaining a representative subset of data.
• Testing if the mean values of two groups are statistically different.

Q2. Which of the following data type conversions may be not allowed in R?

• integer (like 1L or 2L) to numeric
• character (like `1`, `A`, or `test`) to numeric
• logical (like TRUE or FALSE) to numeric
• numeric (like 1 or 2) to integer

Q3. What is the result of the R expression 100 * (5 – 3)?

• 503
• 200
• 497
• 500

Q4. After you write code in an R script file or the R Console, what component of the R environment parses the code into objects in memory?

• R Interpreter
• R variables, functions, and datasets
• R data files
• R Workspace

Q5. Which features of RStudio help facilitate code writing? Select two answers.

• Workspace visualization
• Syntax highlighting
• Code auto completion
• File Explorer

Q6. True or False: Execution order does not matter when executing cells in a Jupyter notebook

• True
• False

Introduction to R Programming for Data Science Week 02 Quiz Answers

Q1. What is a nominal factor?

• A factor with any type or number of elements.
• A factor with ordering.
• A factor with no implied order.
• A factor that contains numeric data.

Q2. Assume that the variable test_result contains the vector c(25, 35, 40, 50, 75).What is the result of the expression mean(test_result)?

• 50
• 35
• 45
• 40

Q3. Assume you have variable called employee that contains the expression list(name = “Juan”, age = 30). What is the correct command to change the contents of the age item to 35?

• employee[age] = 35
• employee[age] <- 35
• employee[“age”] == 35
• employee[“age”] <- 35

Q4. What is the main difference between a matrix and an array?

• A matrix can contain multiple types of data, but an array can only contain data of the same type.
• A matrix must be two-dimensional, but an array can be single, two-dimensional, or more than two-dimensional.
• A matrix can contain vectors, but an array can only contain strings, characters, or integers.
• A matrix can be arranged by rows or columns, but an array is always arranged by columns.

Q5. Assume that you have a data frame called employee that contains three variables: name, age, and title. If you want to return all the values in the title variable, what command should you use?

• employee.title
• employee[3]
• employee$title
• employee[title]

Introduction to R Programming for Data Science Week 03 Quiz Answers

Q1. What is the result of the conditional statement 25 > 15 | 99 >= 100?

• TRUE
• FALSE

Q2. How do you define a global variable in a function?

• Use the == assignment operator.
• Use the -> assignment operator.
• Use the <- assignment operator.
• Use the <<- assignment operator.

Q3. You can use the str_sub() function to form a substring by counting back from the last position. This function is part of which package?

• readr
• stringr
• tidyr
• purrr

Q4. Assume you have a data frame that contains a string variable called ‘phone’. The phone numbers in this variable appear in (###) ###-#### or ###-###-#### format. Which feature of R can you use to isolate the area code (the three numbers between the parentheses or the first three numbers)?

• It is not possible to do this using R.
• A regular expression.
• A mathematical operation.
• A string operation.

Q5. When you convert a date in string format to a Date object, what information do you need to pass to the as.Date() function? Select two answers.

• The number of days since January 1, 1970.
• The date format of the string.
• The UNIX format of the string.
• The string containing the date.

Q6. What is the difference between an error and a warning in your R code?

• An error halts code execution, while a warning does not.
• You can catch an error, but you cannot catch a warning.
• A warning halts code execution, while an error does not.
• You can catch a warning, but you cannot catch an error.

Introduction to R Programming for Data Science Week 04 Quiz Answers

Q1. Assume you have read a .csv file into a data frame variable called employee. It has 20 rows of data and three variables: name, age, and title. What is the correct statement to use to return the fifth row of data in the name and title columns?

• employee[5, 2:3]
• employee[c(“name”, “title”), 5]
• employee[2:3, 1:5]
• employee[5, c(“name”, “title”)]

Q2. How do you return the number of characters in each paragraph of a text file that has been read into a character vector?

• Use the nchar() function.
• Use the file.size() function.
• Use the scan() function.
• Use the length() function.

Q3. Which package do you need to install before writing to an Excel file in R?

• writexlsx
• writexl
• xlsx
• No package is needed. This functionality is built into R.

Q4. You want to get a resource by its URL using an HTTP request and assign the HTTP response containing status code, headers, response body to a response variable. Which function should you use?

• response <-POST(“https://www.mysite.com”)
• response <-HEAD(“https://www.mysite.com”)
• response <-PUT(“https://www.mysite.com”)
• response <- GET(“https://www.mysite.com”)

Q5. After reading an HTML page from a URL, what must you do to get the <body> node from the root <html> node?

• Use the html_node() function to return the <html> node.
• Use the html_text() function to return the <body> node of the HTML.
• Use the html_node() function to return the <body> as a child node of <html> node.
• Use the html_text() function to return the <html> node.

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