This report presents two applications of the Chi-Square test using R: Chi-Square Test for Independence, applied to the UC Berkeley admissions dataset (UCBAdmissions), to determine whether there is a significant relationship between gender and admission status. Chi-Square Goodness-of-Fit Test, applied to the Hair and Eye Color dataset (HairEyeColor), to evaluate whether the distribution of eye colors follows a uniform distribution. The analysis includes data exploration, computation of Chi-Square statistics, p-values, degrees of freedom, and interpretations of the results to support statistical decision-making.

Flow Control Statements

This document presents a simulation of the uniform distribution using R. It demonstrates how to generate random numbers within a specified range, visualize the distribution using a histogram, and interpret the results. The code includes reproducibility using set.seed() and showcases key statistical properties of the uniform distribution.

This R Markdown report demonstrates how to filter and analyze customer transaction data using the dplyr package in R. Specifically, it identifies customers aged over 50 who made purchases exceeding $500 within the past year. The report also includes a data visualization using ggplot2, which presents a boxplot of purchase amount distributions across different regions. The analysis offers insights into high-value customer behavior and regional sales trends, supporting data-driven decision-making in retail or marketing strategies.

For this activity, I worked with a dataset on White Browed Sparrow Weaver nesting, applying logistic regression and data visualization using R.