Publications by Huy Tran
DoE_Week4_Q2
#Problem 1: data.gm <- c(76,76.6,67,75.8,63,74.8) # sample mean of treatment combinations data.r <- rep(6,6) # number of samples for treatment combinations n <- sum(data.r) # total number of samples a <-3 # number of treatments of factor A - brand b <- 2 # number of treatments of factor B - Power of the microwave r = 6 #number of repetitio...
600 sym R (1055 sym/15 pcs)
MA 4720- DoE week 5
Problem 1 For a balanced \(2×3×2\) factorial experiment. For the three-way complete model, write out the contrast of the difference between the effect of level 3 and the average of effects of levels 1 and 2 of factor \(B\) in terms of \(\beta_j^*\). Then write out its contrast coefficients in terms of \(\beta_j^*\). First let’s create a dat...
2814 sym R (2436 sym/8 pcs)
Week 6 HW
Problem 1 AIR <- read.table(file = "C:/Users/justa/Documents/MA 4720 Note/data file/air.velocity.txt", header = TRUE, stringsAsFactors = FALSE) AIR.coe <- read.table(file = "C:/Users/justa/Documents/MA 4720 Note/data file/air.velocity.contrasts.txt", header = TRUE, stringsAsFactors = FALSE) AIR; AIR.coe ## AirVeloc RibHt ReyNo ## 1 ...
3245 sym R (71937 sym/256 pcs) 10 img
Week 6 Quiz 1
Problem 1 Week 6 Quiz 1 Problem 1 (Air Velocity Experiment) (15 points). A set of 17 orthogonal contrasts based on trends are constructed and normalized. The least squares estimates of these 17 contrasts are obtained and listed according to their absolute values. Find corresponding half-normal score, complete the following table and draw a half-n...
1186 sym R (2096 sym/6 pcs) 1 img
Tran_Week5_HW
Problem 5.1 Data for visualize, note it will not have an assigned specific amount of replication to it. ## Warning: package 'janitor' was built under R version 4.0.5 ## trtmt n percent ## 111 1 0.05555556 ## 112 1 0.05555556 ## 121 1 0.05555556 ## 122 1 0.05555556 ## 131 1 0.05555556 ## 132 1 0.05555556 ## 211 1 0....
10873 sym R (9519 sym/61 pcs) 3 img
Tran_Week6_Quizz 2
Problem 1: Use R program to conduct the randomization for a randomized complete block design with \(v=3\) treatments observed once \((s=1)\) in each of \(b=4\) blocks. set.seed(1) v= 3 b=4 s=1 rand.order = matrix(rep(c(1:v),s), nrow =v*s, ncol= b ) rand.order = apply(X = rand.order, FUN = sample, MARGIN = 2) rand.order; t(rand.order) ## ...
2618 sym R (2100 sym/15 pcs) 1 img