To determine if there is a significant difference between the means or medians of two or more groups in R, you should compare groups. By comparing groups, you can identify patterns or trends in the data and see how different factors affect the outcome of interest. Now, let’s see how to compare groups in R and … Read more
R is a programming language for statistical computing and graphics and is constantly being updated and improved. It is essential to keep track of the version of R that you are using, as different versions may have additional features and capabilities. If you are working with a script or package written for a specific R … Read more
There are four forms of the extract operator in R: [, [[, $, and @. The fourth form is the slot operator and is used to extract content from objects built with the S4 object system, also known as a formally defined object in R. Most beginning R users don’t work with formally defined objects, … Read more
Building a list of multiple elements over time is helpful. If you need to create a list of names, emails, and phone numbers and then append all of these lists together to create a single list, you require some methods or approaches to do that. How to Append Multiple Elements to a List in R … Read more
Vectors are the primary data type in R and can store multiple values of the same data type. Vectors can store and manipulate data consistently and efficiently. R append multiple elements to a vector There are 3 easy ways to append multiple elements to a Vector in R. Using the c() function: The c() function … Read more
The exponential distribution is a continuous probability distribution that defines the time between events in a process that occurs continuously and independently at a constant average rate. Generate Exponentially Distributed Random Numbers in R To generate exponentially distributed random numbers in R, use the rexp() function. The rexp() is a built-in R function that returns the … Read more
Binomial distribution has two possible outcomes in statistics. Success Failure The probability of success (p) and failure (1 – p) are fixed and do not change from one trial to the next. The number of successes (x) in a given number of trials (n) follows a binomial distribution. A binomial random number is a random … Read more
The normal distribution is a continuous probability distribution defined by its mean and standard deviation. It is also known as the Gaussian distribution or bell curve because of its characteristic shape. Generate Normal Distribution Random Numbers in R To generate random numbers from a normal distribution in R, use the rnorm() function. The rnorm() function … Read more
The uniform distribution in R is a continuous probability distribution with a flat shape, while the normal distribution is a continuous probability distribution with a bell-shaped curve. Generating Uniformly Distributed Random Numbers in R To generate uniformly distributed random numbers in R, use the runif() function. The runif() is a built-in R function that generates random numbers … Read more
The pnorm() function offers the distribution function. The qnorm() function provides the quantile function. Finally, the rnorm() function generates random deviates. In statistics, the normal distribution is characterized by its mean μ and standard deviation σ. dnorm in R The dnorm() is a built-in R function that computes the Probability Density Function (PDF) of the … Read more