Hello,
This may be a rare question. I am struggling to solve it. I really
appreciate any help or suggestions. Thanks a lot in advance!
I put my questions between the code to make it clear. The problem I have is:
I generated 10 data sets with 8 data for each set. Now I want to change the
number of data in each dataset according to a vector 'size' (as follows),
that is, each new dataset contains different number of data. How can I do
it? After generating the new datasets, how can I seperate the data from two
distributions and calculate the sample mean? Thanks a lot.
# generate 10 data sets, each data sets include 8 sample. 4 from N(0, 1) and
4 from N(5, 1)
data<- matrix(0,10,8)
th <- c(0, 5, 1)
for(i in 1:10){
data[i,] <- rnorm(8,mean= rep(th[1:2],8/2),sd=th[3])
}
# change the number of samples for each data set. e.g. the first dataset
needs to increase to 20, the #first 8 keep the same, add another 12 sample
(6 from N(0,1) and the other 6 from N(5, 1) ), the second #dataset needs to
increase to 10, keep the first 8 the same, generate another 2 (one from
N(0,1) and the #other one from N(5,1)), the third data set does not need to
change. etc.
size=c(20, 10, 8, 14, 16, 12, 8, 80)
# Since each data set changes to different size, and add different number of
data, for each dataset how #can I calculate the difference of the sample
mean from N(0,1) and the sample mean from
#N(5,1) and the pooled standard deviation of two samples. Two difficulties:
each new dataset includes #different number of data; another difficulty,
when I generated data, the two successive data are
#from different normal distribution, how can I seperate them and calculate
the average for each sample #and pooled standard deviation?
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