Imagine you need to create a function in R that checks if a number is prime. How would you do this?
- is_prime <- function(n) { if (n <= 1) { return(FALSE) } for (i in 2:sqrt(n)) { if (n %% i == 0) { return(FALSE) } } return(TRUE) }
- is_prime <- function(n) { if (n <= 1) { return(TRUE) } for (i in 2:sqrt(n)) { if (n %% i == 0) { return(TRUE) } } return(FALSE) }
- is_prime <- function(n) { if (n <= 1) { return(FALSE) } for (i in 2:sqrt(n)) { if (n %% i != 0) { return(TRUE) } } return(FALSE) }
- All of the above
To create a function in R that checks if a number is prime, you can use the following code: is_prime <- function(n) { if (n <= 1) { return(FALSE) } for (i in 2:sqrt(n)) { if (n %% i == 0) { return(FALSE) } } return(TRUE) }. The function takes a number n as input and iterates from 2 to the square root of n, checking if any of these numbers divides n. If a divisor is found, the function returns FALSE; otherwise, it returns TRUE.
Can you describe a situation where you would need to use logical operations in R?
- Checking conditions in control flow statements
- Filtering data based on specific criteria
- Creating boolean variables for flagging
- All of the above
Logical operations in R are commonly used in situations such as checking conditions in control flow statements, filtering data based on specific criteria, and creating boolean variables for flagging or indicating certain conditions.
In R, the operator != is used to check if two values are ________.
- equal
- not equal
- less than
- greater than
In R, the operator != is used to check if two values are not equal. For example, 3 != 4 would return TRUE.
In R, the ______ function can be used to combine several vectors into one.
- cbind()
- rbind()
- merge()
- combine()
In R, the rbind() function can be used to combine several vectors into one. The rbind() function combines vectors by binding them row-wise, creating a new vector with the elements from each input vector arranged in rows.
How does R internally store different types of variables such as vectors, lists, and data frames?
- In RAM
- In the processor cache
- None of the above
- On the hard disk
R stores all variables in RAM (Random Access Memory). This includes vectors, lists, data frames, and other data structures. This is part of what allows R to perform operations on data very quickly, but it also means that R can be memory-intensive, especially when working with large datasets.
The ______ parameter in the bar chart function in R can be used to create a horizontal bar chart.
- col
- names.arg
- horiz
- colors
The horiz parameter in the bar chart function in R can be used to create a horizontal bar chart. By setting the horiz parameter to TRUE, the bars will be displayed horizontally, providing a different orientation for the chart.
Suppose you have a vector of strings in R and you need to concatenate them into a single string. How would you do that?
- Use the combine() function
- Use the concat() function
- Use the merge() function
- Use the paste() function with collapse argument
In R, we can use the paste() function with the collapse argument to concatenate a vector of strings into a single string. For example, paste(c("Hello", "World"), collapse = " ") would return "Hello World".
To determine the number of characters in a string, you can use the ________ function in R.
- len()
- length()
- nchar()
- strlen()
In R, the nchar() function is used to determine the number of characters in a string. For example, nchar("Hello") would return 5.
What function is commonly used to create a basic scatter plot in R?
- scatterplot()
- plot()
- points()
- scatter()
The plot() function is commonly used to create a basic scatter plot in R. It can be used to visualize the relationship between two numeric variables by plotting the data points as individual points on the graph.
In R, a variable that contains a sequence of data is called a ________.
- DataFrame
- List
- Matrix
- Vector
A vector in R is a sequence of data elements of the same basic type. Members in a vector are officially called components. However, R also has other data structures like lists, matrix, and dataframe which can hold multiple data types or more complex data.