The function to generate random numbers in R following a normal distribution is ________.
- generate_random()
- randn()
- random()
- rnorm()
The rnorm() function in R is used to generate random numbers following a normal distribution. For example, rnorm(10) would generate 10 random numbers from a standard normal distribution.
Imagine you need to create a bar chart in R that color-codes bars based on a specific criteria. How would you do this?
- Use the barplot() function and provide a vector of colors corresponding to each bar
- Use the pie() function and provide a vector of colors corresponding to each segment
- Use the plot() function and specify the colors parameter
- Use the ggplot2 package and the geom_bar() function with the fill aesthetic
To create a bar chart in R that color-codes bars based on a specific criteria, you would use the barplot() function. Provide a vector of colors corresponding to each bar, ensuring that the colors align with the specific criteria you want to represent.
How does R handle operator precedence when both 'AND' and 'OR' are used in a single expression?
- R follows the standard operator precedence, where 'AND' takes precedence over 'OR'
- R follows the standard operator precedence, where 'OR' takes precedence over 'AND'
- R gives equal precedence to 'AND' and 'OR', evaluating them left to right
- The precedence depends on the context and cannot be determined
When both 'AND' and 'OR' operators are used in a single expression, R follows the standard operator precedence rules. The 'AND' operator ('&') takes precedence over the 'OR' operator ('
The R function to calculate the factorial of a number is ________.
- fact()
- factorial()
- multiplication()
- product()
The factorial() function in R is used to calculate the factorial of a number. For example, factorial(5) would return 120 because 5 factorial (5!) is 54321 = 120.
What are some strategies for handling non-normal data in statistical analyses in R?
- Transforming the data
- Using non-parametric tests
- Employing robust statistical methods
- All of the above
All of the mentioned strategies can be used for handling non-normal data in statistical analyses in R. Transforming the data (e.g., logarithmic or power transformations) can make it conform to normality assumptions. Non-parametric tests, which do not rely on specific distribution assumptions, can be used instead of parametric tests. Robust statistical methods are designed to be less sensitive to deviations from normality and can provide more reliable results in such cases. The choice of strategy depends on the characteristics of the data and the research question.
Imagine you need to calculate the average of all the numbers in a list using a for loop in R. How would you do this?
- total <- 0; count <- 0; for (num in list) { total <- total + num; count <- count + 1 }; average <- total / count;
- average <- 0; for (num in list) { average <- average + num / length(list) }
- average <- 0; count <- 0; for (num in list) { average <- (average * count + num) / (count + 1); count <- count + 1 }
- average <- sum(list) / length(list)
To calculate the average of all the numbers in a list using a for loop, you can initialize variables total and count to 0. Then, iterate over each number in the list, updating total by adding the current number and incrementing count by 1. Finally, calculate the average by dividing total by count.
A ________ is a special type of vector in R that can contain elements of different classes.
- Character Vector
- List
- Logical Vector
- Numeric Vector
A list in R, though similar in some ways to a vector, can contain elements of different classes - numbers, characters, vectors, and even other lists.
To filter rows in a data frame in R based on a condition, you would use the ______ function.
- filter()
- subset()
- select()
- extract()
To filter rows in a data frame in R based on a condition, you would use the filter() function. The filter() function allows you to specify a condition or logical expression to select rows that meet the specified criteria, creating a subset of the data frame.
To customize the markers in an R scatter plot, you would use the ______ parameter.
- col
- pch
- cex
- marker
To customize the markers in an R scatter plot, you would use the pch parameter. It allows you to specify a numerical value or character that represents the marker type for the data points, such as circles, squares, triangles, or custom symbols.
What is the purpose of a while loop in R?
- To repeat a block of code as long as a certain condition is true
- To iterate over a sequence of values
- To execute a block of code a specific number of times
- To break out of a loop when a condition is met
The purpose of a while loop in R is to repeat a block of code as long as a certain condition is true. The loop continues until the condition becomes false. This allows for repetitive execution of code based on a specific condition.