Exploring R

    Hello all 👋 In this blog post, we will explore the world of Object-Oriented Programming (OOP) in R. Specifically, we will assign S3 and S4 classes to the ToothGrowth dataset, a well-known dataset in R. Through this exploration, we aim to understand how these OOP systems work and how they can be applied to datasets. Additionally, we will discuss the implications of using these systems for data analysis workflows. The Effect of Vitamin C on Tooth Growth in Guinea Pigs Description The response is the length of odontoblasts (cells responsible for tooth growth) in 60 guinea pigs. Each animal received one of three dose levels of vitamin C (0.5, 1, and 2 mg/day) by one of two delivery methods, orange juice or ascorbic acid (a form of vitamin C and coded as  VC ). Format A data frame with 60 observations on 3 variables. [,1] len numeric Tooth length [,2] supp factor Supplement type (VC or OJ). [,3] dose numeric Dose in milligrams/day Source C. I. Bliss (1952).  Th...

Hello all 😊 In our latest blog entry, we delve into the world of matrix operations in the R programming language. We'll cover fundamental concepts like matrix addition, subtraction, and generation. Please check this URL |  Matrix Mathematical Operations  | for the code for the below operations -To find the sum of matrices A and B, we use the '+' operator -To find the difference between matrices A and B, we use the '-' operator -To create a diagonal matrix of size 4 with the values 4, 1, 2, and 3 along the diagonal using the diag() function. - The sweep() function in R performs operations across rows or columns of matrices. Applies a function to rows or columns of a matrix while specifying a margin for the operation.

 Hello all, In this blog post, we will explore the concepts of determinants and inverses of matrices using R, including their significance and practical implications. In R, we can compute the determinant using the "det()" function and inverse using the "solve()" function. In our code snippet, we can observe that the matrix is a square matrix. The determinant of matrix A turned out to be zero, indicating that it is singular. The formula for the inverse of the matrix is A−1 = adj A / |A| where adj A is the adjoint matrix and |A| is the determinant of A. Since the determinant of A is zero and the inverse of zero can not be determined R is throwing an error. In the case of the B Matrix,  we encountered errors again because  the computation of the determinant failed because B is not a square matrix. In addition, the inversion failed due to the non-square dimensions of B. Please find my R code via this URL |  Matrix. R  |