Publications by Hossein Bahreinizad
Homework 5
1 3.7 #reading and formating the data MT1 <-c(3129,3000,2865,2890) MT2 <-c(3200,3300,2975,3150) MT3 <-c(2800,2900,2985,3050) MT4 <-c(2600,2700,2600,2765) dat <-data.frame(cbind(MT1,MT2,MT3,MT4)) stacked_dat <- stack(dat) 1.1 c) anova_results <- aov(values~ind,dat = stacked_dat)#ANOVA summary(anova_results) #ANOVA output ## Df...
1774 sym R (4259 sym/20 pcs) 7 img
FA10 Group6
0.1 a) \(y_{ij}=\mu+\tau_i+\epsilon_{ij}\) \(H_0:\mu_1=\mu_2=\mu_3=\mu_4\) \(H_1\):at least one \(\mu\) is different 0.2 b) #Inputing and formating the data M1 <- c(.34,.12,1.23,.70,1.75,.12) M2 <- c(.91,2.94,2.14,2.36,2.86,4.55) M3 <- c(6.31,8.37,9.75,6.09,9.82,7.24) M4 <- c(17.15,11.82,10.97,17.20,14.35,16.82) dat <- data.frame(cbind(M1,M...
606 sym R (981 sym/9 pcs) 4 img
HW6
1 3.23 #reading the data ft1 <- c(17.6,18.9,16.3,17.4,20.1,21.6) ft2 <- c(16.9,15.3,18.6,17.1,19.5,20.3) ft3 <- c(21.4,23.6,19.4,18.5,20.5,22.3) ft4 <- c(19.3,21.1,16.9,17.5,18.3,19.8) data <- as.data.frame(cbind(ft1,ft2,ft3,ft4)) stacked_data <- stack(data) 1.1 a) model <- aov(values~ind,data = stacked_data) summary(model) ## ...
2125 sym 12 img
FA11_Group7
1 Question 1 \(H_0:\mu_1=\mu_2=\mu_3=\mu_4=\mu\) \(H_1:\)at least one of the \(\mu_i\) differs Fixed effect hypothesis: \(H_0:\tau_i=0\) \(H_1:\tau_i\neq0\) Linear effect model: \(y_{ij}=\mu+\tau_i+\beta_j+e_{ij}\) library(GAD) chemical<-c(rep(1,5),rep(2,5),rep(3,5),rep(4,5)) chemical ## [1] 1 1 1 1 1 2 2 2 2 2 3 3 3 3 3 4 4 4 4 4 bolt<-c(seq(...
1396 sym R (1278 sym/14 pcs)
FA12_group5
1 Question 1 Yes, it is a valid latin square. For a valid latin sqaure, we need orthoganality. Meaning none of the latin letters should repeat in each row or column, which is satisfied here. 2 Question 2 Model equation: \(X_{ijk}=\mu+\tau_i+\beta{j}+\alpha_k+\epsilon_{ijk}\) where \(\mu\) is the grand mean, \(\tau_i\) is the factor (ingredien...
819 sym
Document
4.3 \(H_0:\tau_i=0\) \(H_1:\tau_i\neq0\) chemical<-c(rep(1,5),rep(2,5),rep(3,5),rep(4,5)) chemical <- as.factor(chemical) bolt<-c(seq(1,5),seq(1,5),seq(1,5),seq(1,5)) bolt <- as.factor(bolt) ob <- c(73,68,74,71,67,73,67,75,72,70,75,68,78,73,68,73,71,75,75,69) dat <- data.frame(ob,chemical,bolt) model <- aov(ob~chemical+bolt,data = dat) sum...
914 sym
Midterm_question6
data <- read.csv("zoombies(1).csv") Question 1 boxplot(data$Basic,data$Conehead,data$Buckethead,names = c('basic','conehead','buckhead')) From these plots we can guess the means of three populations are different, but their variance seems to be about the same. Question 2 \(H_0: \mu_1=\mu_2=\mu_3\) \(H_1:\) at least one \(\mu\) differs data1 <...
932 sym 4 img
FA14_group1
Q1 a) \(X_{ijk}=\mu+\alpha_i+\beta_j+\gamma_k+\alpha\beta_{ij}+\beta\gamma_{jk}+\alpha\gamma_{ik}+\alpha\beta\gamma_{ijk}+\epsilon_{ijk}\) b) library(GAD) data=read.csv("https://raw.githubusercontent.com/tmatis12/datafiles/main/PowderProduction.csv") Ammonium <- as.fixed(data$Ammonium) Temperature <- as.fixed(data$Temperature) StirRate <- as...
1306 sym R (3403 sym/13 pcs) 1 img
HW10
5.4 feedrate <- c(rep(0.2,3),rep(0.25,3),rep(0.3,3),rep(0.2,3),rep(0.25,3),rep(0.3,3),rep(0.2,3),rep(0.25,3),rep(0.3,3),rep(0.2,3),rep(0.25,3),rep(0.3,3)) depth <- c(rep(0.15,9),rep(0.18,9),rep(0.20,9),rep(0.25,9)) obs <- c(74,64,60,92,86,88,99,98,102,79,68,73,98,104,88,104,99,95,82,88,92,99,108,95,108,110,99,99,104,96,104,110,99,114,111,107) ...
831 sym R (4342 sym/17 pcs) 2 img 1 tbl
FA16_group4
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(rep(-1,4),rep(1,4),rep(-1,4),rep(1,4)) D <- c(rep(-1,8),rep(1,8)) obs <- c(12,18,13,16,17,15,20,15,10,25,13,24,19,21,17,23) data <- data.frame(A,B,C,D,obs) a) library(DoE.base) model <- lm(obs~A*B*C*D,data = data) halfnormal(mode...
331 sym R (870 sym/4 pcs) 1 img