This week, I had the opportunity to create the foundation of my first R package as part of Module #10 in Dr. Friedman’s class. The assignment focused on understanding the structure of an R package and writing a complete DESCRIPTION file—an essential component that documents a package’s metadata and dependencies. I named the package Friedman, […]
Hello again. This week it is visualization week! I enjoyed this assignment this week because it allowed me to explore the artistic side of data while comparing three powerful visualization techniques in R. The dataset I selected, Anscombe’s Quartet, was ideal for this exercise because it is simple, compact, and visually rich despite having no […]
Input/Output, string manipulation and plyr package Please 📂 Check out my full code on GitHub! Dataset: This assignment gave me a deeper understanding of how R handles data types and why the right approach matters. My first challenge was realizing that getting the average by the Student gender using the command mean(Sex) didn’t work because [Sex] […]
R is a powerhouse for data analysis, and its Object-Oriented (OO) systems—S3 and S4—offer flexible ways to structure data. Through this adventure of debugging, testing, and optimizing functions, I have explored both systems hands-on. Here’s a breakdown of what I learned! How Do We Determine If a Generic Function Can Be Used? A dataset supports […]
Hello! This post explores matrix operations in R, specifically focusing on: Let’s dive into hands-on R coding and learn how these fundamental concepts power data transformations!NOTE: 📂 Check out my full code on GitHub! 1. Matrix Addition and Subtraction We start by defining two matrices: # Define matrices A and B A <- matrix(c(2, 0, 1, […]
Welcome back to my analytics journey. Today, I’m tackling Module 5, where we explore matrices in R—specifically, how to find their inverse and determinant. But here’s the catch… not all matrices play nice! Let’s break it down. 📌 The Challenge: Can These Matrices Be Inverted? We were given two matrices: A <- matrix(1:100, nrow=10) # […]
Lessons from Module 4 This module was all about structured programming in R, and honestly, it made life easier. Instead of messy, repetitive code, we used functions to simplify our workflow, making everything clean, reusable, and scalable. The case study? A hospital dataset where we analyzed blood pressure (BP) readings and doctor assessments. Here’s what […]
Hello again! This week, we are exploring Data Frames in R. According to The Art of R Programming (Matloff, p. 35), “A data frame in R is a list, with each component of the list being a vector corresponding to a column in our ‘matrix’ of data.” What is a Data Frame? A matrix is […]
Hey everyone! I explored R functions using a simple one from this week’s assignment to calculate the mean of a numeric vector. Initially, the function was straightforward: sum up the values and divide by the count. Running the function gave me a result of 19.25—pretty cool, right? The function provided by Professor myMean() worked because […]
Hello, I am back to learn more about R programming. My future code will be uploaded to GitHub. Let’s have fun this year coding with R. I will be posting more about my projects soon.
Everyday Stat, Analytics & Python 