Week 12 Assignment – 100 points Objective: Using Logistic Regression to handle a binary outcome. Given the prostate cancer dataset, in which biopsy results are given for 97 men: • You are to predict tumor spread in this dataset of 97 men who had undergone a biopsy. • The measures to be used for prediction are: age, lbph, lcp, gleason, and lpsa. This implies that binary dependent variable of lcavol will be the outcome variable. We start by loading the appropriate libraries in R: ROCR, ggplot2, and aod packages as follows: > install.packages(“ROCR”) > install.packages(“ggplot2”) > install.packages(“aod”) > library(ROCR) > library(ggplot2) > library(aod) Next, we load the csv file and check the statistical properties of the csv File as follow: > setwd(“C:/RData”) # your working directory > tumor <- read.csv(“prostate.csv”) # loading the file > str(tumor) # check the properties of the file . . . continue from here! Reference R Documentation (2016: 2024 – Do my homework – Help write my assignment online). Prostate cancer data. Retrieved from http://rafalab.github.io/pages/649/prostate.html
The Evolution of U.S. Global Engagement/df1r
The United States and Global Engagement: A Historical and Personal Analysis [Your Name] [Date] The engagement of the United States with the world has taken various forms throughout history, encompassing political, economic, and military interactions. From early diplomatic efforts to contemporary international relations, these engagements have shaped global dynamics in significant ways. One crucial aspect […]
