Generating 100 uniform different random variables in R code

Question

I am trying to generate 100 samples of Z, where Z is the summation of 8 independent uniformly distributed random variables in the interval [0;1]

I have the following code so far, but I'm not sure if it's correct. I am not sure if my loop is correct

eight<-runif(8,0,1) #Uses the runif function to generate 8 uniform 0-1 random variables
   Z_1<-sum(eight)  #caclulates the sum and stores it in the variable Z_1
   sample <-NA


   for (i in 1:100 ) {  #Function continues the loop for 100 different values 
      eight<-runif(8,0,1); #Creates sum loop for 8 independent values uniform 0-1 random variables.
      Z_1<-sum(eight); # stores in the sum loop in the variable Z
      sample[i] = Z_1;
    }`

Thanks

Answer 1

I would vectorize the whole thing. There is no real reason to run 100 iterations when you can just generate 800 observations in one run. Then just use matrix and colSums and you done

set.seed(123)
n <- 100
Z <- colSums(matrix(runif(8 * n), 8, n))
Z
#  [1] 4.774425 4.671171 4.787691 4.804041 3.513257 2.330163 3.300135 3.568657 5.503481 2.861764 4.533283 3.353658
# [13] 4.230073 4.690739 4.364708 3.094156 4.933616 3.942834 3.712522 2.587036 3.731474 4.388749 4.484030 4.315968
# [25] 4.800758 4.252631 2.716972 5.159044 4.146881 3.244546 4.418618 4.350035 5.344182 3.176801 3.903337 2.261935
# [37] 3.646572 4.286075 3.074900 4.210506 3.172513 4.535665 4.245856 4.184848 4.532286 2.899883 4.473629 4.751224
# [49] 3.498038 3.337437 4.238989 3.349812 3.888696 4.748254 3.029479 4.246619 3.330434 3.879168 3.786216 3.839956
# [61] 3.878997 4.546531 2.863010 3.417072 4.266108 3.141875 4.960758 3.989613 4.373042 4.295742 4.459014 5.561066
# [73] 4.401990 4.121301 3.830575 3.412446 3.812347 5.591238 3.801587 4.454336 4.213343 5.222007 4.300991 2.765003
# [85] 3.293251 5.362586 2.954080 3.036312 3.655677 3.373603 5.575184 4.167740 3.904038 3.884440 2.901452 3.079311
# [97] 4.927770 3.930943 4.169907 2.922618