Publications by Sith
PCA and Eigenspace
Principal Components & Eigenspace Hi, Team! Many of your are struggling with the concept of principal components (PCs) & Eigenspace. I am going to break it down, starting with principal components. The Process of Generating Components In principal component analysis (PCA), we seek to iteratively generate a linear combination of weighted columns...
4244 sym
HW 5 Spring 2023
Function to Reject or Not myp=function(p, alpha){ifelse(p<alpha, return(noquote('REJECT Ho')),return(noquote('FAIL 2 REJECT')))} Function for Shading Normal shadenorm = function(below=NULL, above=NULL, pcts = c(0.025,0.975), mu=0, sig=1, numpts = 500, color = "gray", dens = 40, j...
5583 sym Python (8561 sym/62 pcs) 10 img
One-Way ANOVA
The Analysis of Variance (ANOVA) Hi, Team! Many of your are struggling with the concept of the One-Way Analysis of Variance (ANOVA), so I am going to break it down for you. The ANOVA test is actually a set of methods that break down the variance of the model versus the variance of of the residual. ANOVA is used in experimental design, Design of ...
13086 sym Python (5147 sym/25 pcs) 3 img
BC Week 4 & 5 Discussion
The Chi Square Distribution versus a Proportion Test Hi, Team! Some of you have likely noticed that the results provided by prop.test in R do not include the Guassian probability and do include (by default) a corrected \(\chi^2\). The \(\chi^2\) is actually the distribution for a variance, so it is strictly positive. If we have observed and expe...
9935 sym Python (6442 sym/33 pcs) 3 img
Example for Week 1
Library & Split library(ggplot2) ## Warning: package 'ggplot2' was built under R version 4.2.2 setosa <- iris[iris$Species=="setosa",] versicolor <- iris[iris$Species=="versicolor",] virginica <- iris[iris$Species=="virginica",] Setosa Summary summary(setosa) ## Sepal.Length Sepal.Width Petal.Length Petal.Width ## Min. :4.30...
680 sym R (6953 sym/34 pcs) 20 img
True Colors for Kim
Load Data library(psych) ## Warning: package 'psych' was built under R version 4.0.5 setwd("D:/kim graphs") compdata=read.csv("kim study.csv", stringsAsFactors = T) compdata$Gender=as.factor(compdata$Gender) levels(compdata$Gender)=c("Female", "Male") Describe Data describe(compdata[,2:length(compdata)]) ## vars n mean sd ...
570 sym R (10172 sym/26 pcs) 9 img
Ram
Load Library & Data library(nloptr) library(rgdal) ## Warning: package 'rgdal' was built under R version 4.2.2 ## Loading required package: sp ## Warning: package 'sp' was built under R version 4.2.2 ## Please note that rgdal will be retired during 2023, ## plan transition to sf/stars/terra functions using GDAL and PROJ ## at your earliest con...
309 sym R (14132 sym/42 pcs)
VertAg
Load Parameters #plants = tomatoes, green beans, kale b=100 #b=buildings: will replace this with the actual number of building y=30 #y=years: running for a 30-year lifespan i=30 #i=iterations: number of iterations Storage of Results / Seed Initialization #matrices to hold results yield=matrix(rep(0,i*b*y), c(i,b*y)) co2=matrix(rep(0,i...
120 sym 3 img
EHR
Set Up / Install Libraries Read Data / Map and Impute Missing mydata=read.csv("output.csv") missmap(mydata) mynames=colnames(mydata) #Check Columns for missing a=rep(0,ncol(mydata)) for (i in 1:ncol(mydata)){ a[i]=1-sum(is.na(mydata[,i])==TRUE)/nrow(mydata) } names(a)=mynames min(a) ## [1] 0.8897638 #Check Rows for missing b=rep(0,n...
289 sym R (25908 sym/43 pcs) 6 img
Veterans
Setup Read Data #mydata=read.xport("C:/users/lfult/desktop/jose/LLCP2018.xpt") #write.csv(mydata,"C:/users/lfult/desktop/jose/reloaded.csv", row.names=FALSE ) Pre-Processed and Reduced mydata=read.csv("C:/users/lfult/desktop/jose/reduced.csv") myprop=read.csv("C:/users/lfult/desktop/jose/for mapping final.csv") myprop$state=myprop$State mypr...
375 sym R (15150 sym/103 pcs) 2 img