Publications by Luis Araiza, Yashwanth Dommaraju, Syed Mustafa Ahmed
Flipped Assignment 3 Group 5
Purpose The purpose of this analysis is to to compare the resting heartbeats of males and females. Basic Filtering At first the raw data was separated into 2 dataframes with datf listing a range of female heartbeats and datm for male heartbeats. dat <- read.csv("https://raw.githubusercontent.com/tmatis12/datafiles/main/normtemp.csv") # 1 is mal...
2205 sym 5 img
Flipped Assignment 4
title: “FLipped Assignment 4” author: “Luis Araiza, Yashwanth Dommaraju,Mustafa Ahmed Syed” date: “9/8/2022” output: html_document Set up Here the csv was read and put into a dataframe dat <- read.csv("https://raw.githubusercontent.com/tmatis12/datafiles/main/US_Japanese_Cars.csv") Question 1 # Normal Probablillity Plot of US cars ...
1500 sym 6 img
Design of Experiments HW 1 Luis Araiza
Question 2.24 2.24A The null hypothesis is that the means are equal between the machines. While the alternative is that there is a non-zero difference. ## Question 2.24b a t-test is performed to test the hypothesis mac1 <- c(16.03,16.04,16.05,16.05,16.02,16.01,15.96,15.98,16.02,15.99) mac2 <- c(16.02,15.97,15.96,16.01,15.99,16.03,16.04,16.02...
1933 sym Python (4808 sym/14 pcs) 4 img
Week 6 HW Luis Araiza
Problem 3.23 Preperation f1 <- c(17.6, 18.9, 16.3, 17.4, 20.1, 21.6) resf1 <- f1- mean(f1) f2 <- c(16.9, 15.3, 18.6, 17.1, 19.5, 20.3) resf2 <- f2- mean(f2) f3 <- c(21.4, 23.6, 19.4, 18.5, 20.5, 22.3) resf3 <- f3- mean(f3) f4 <- c(19.3, 21.1, 16.9, 17.5, 18.3, 19.8) resf4 <- f4- mean(f4) datf <- data.frame(f1,f2,f3,f4) stackdat <- stack...
2018 sym R (8248 sym/31 pcs) 11 img
Luis Araiza DOE Test 1
Prep game<- c( 1, 2 ,3 ,4 ,5 ,6 ,7 ,8 ,9 ,10 ,11 ,12 ,13 ,14 ,15) game <- as.factor(game) Basic <- c(21, 20, 25, 22, 21, 22, 22, 24, 24, 23, 21, 25, 23, 24, 24) Conehead<-c( 28 ,28 ,25 ,29 ,29 ,27 ,30 ,29 ,29 ,29 ,30 ,26 ,26 ,26 ,28) Buckethead<- c( 23, 23, 23, 21, 21, 22, 20, 22, 22, ...
889 sym R (2023 sym/21 pcs) 5 img
Luis Araiza HW week 9
5.2 Part A DF of source B can be calculated from the following equation DF interaction : $=()() $ the only unknown value is \(\beta\) which comes out to 4. SS_a can be calculated from \(MS_a*DF_a\), which comes out to .0002. the remaining MS values can be solved by dividing the SS values from the respective DF values. The F-stat can be solved b...
966 sym
FA 16 group 1
Data Preperation yield <- c(12,18,13,16,17,15,20,15,10,25,13,24,19,21,17,23) A <- c(-1,1,-1,1,-1,1,-1,1,-1,1,-1,1,-1,1,-1,1) B <- c(-1,-1,1,1,-1,-1,1,1,-1,-1,1,1,-1,-1,1,1) C <- c(-1,-1,-1,-1,1,1,1,1,-1,-1,-1,-1,1,1,1,1) D <- c(-1,-1,-1,-1,-1,-1,-1,-1,1,1,1,1,1,1,1,1) Halfnormal Plot dat <- data.frame(yield,A,B,C,D) #install.packa...
336 sym R (1551 sym/16 pcs) 1 img
FA 18 G3
Model Equation In this nested design the model equation is as follows; Effects = \(\mu + \alpha_i+\beta_j(i)+\epsilon_ijk\) Hypothesis The null hypothesis is that for the burning rates there is no difference in the process used to manufacture them The alternative is that there is at one of the processes is different from the others. Experime...
606 sym R (2050 sym/9 pcs)
Luis Araiza Last HW
Set Up Here the experiment is set up A <- c(1,2) B <- c(1,1,2,2,3,3) Spindle <- c(rep(A,12)) Machine <- c(rep(B,4)) obs <- c(12, 8 ,14, 12, 14, 16, 9, 9, 15, 10, 10, 15, 11, 10, 13, 11, 12, 15, 12, 8, 14, 13, 11, 14) Machine <- as.fixed(Machine) Spindle <- as.random(Spindle) As a nested effect spindle is set t...
262 sym
Q13 Final exam
Question 9 on the carbon anode library(GAD) ## Warning: package 'GAD' was built under R version 4.1.3 ## Loading required package: matrixStats ## Warning: package 'matrixStats' was built under R version 4.1.3 ## Loading required package: R.methodsS3 ## Warning: package 'R.methodsS3' was built under R version 4.1.3 ## R.methodsS3 v1.8.2 (2022-06-1...
1005 sym R (2206 sym/14 pcs)