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Sorry about the subject --- On Thu, 24/9/09, KABELI MEFANE <kabelimefane@yahoo.co.uk> wrote: From: KABELI MEFANE <kabelimefane@yahoo.co.uk> Subject: Re: [R] Multiply Normal Curves To: R-help@r-project.org Date: Thursday, 24 September, 2009, 11:48 AM R -helpers   i have been trying to do this problem without must success,i managed to do a graph for x, but i...

...(x,mean=parms$mu[2],sd=parms$sigma[2]),from=1000, to=80000, ylab="density", col="blue", add=TRUE) curve(dnorm(x,mean=parms$mu[3],sd=parms$sigma[3]),from=1000, to=80000, ylab="density", col="forestgreen", add=TRUE) ### --- On Wed, 23/9/09, KABELI MEFANE <kabelimefane@yahoo.co.uk> wrote: From: KABELI MEFANE <kabelimefane@yahoo.co.uk> Subject: [R] Simulating and Plotting To: R-help@r-project.org Date: Wednesday, 23 September, 2009, 10:32 PM R-helpers   I have been learning a little bit of R. I am simulating and i want to draw a normal curve for all...

Dear All ? I know that you do not have to help me but please do, i am new to R as a CPI compiler, i just need to do a sample to see which sampling method best works in different situations, therefore since this is for practice purposes nobody will finance a real project thats why i need you to help me direct me as to how simulate data (just direct me,not 100% help). See my attachment for problem

R helpers   Please help me combine the simulated data to a form of table where: Hypermarket have 10 rows, supermarket have 15 rows,......., spazashops with 35 rows.   Hypermarket <- rnorm(10, mean=20000, sd=7000) Supermarket <- rnorm(15, mean=12000, sd=4000) Minimarket   <- rnorm(20, mean=10000, sd=4000) Cornershop  <- rnorm(20, mean= 8000, sd=3000) Spazashop   <- rnorm(35, mean=

 Dear All   let me go one step further by asking you if you could help me show that the distribution of this data in normal.  have a little idea (by trial and error) but i seem to not fully understand how its done.   H<-rnorm(100, mean=50000, sd=3000) par(las=1) hist(H, breaks=seq(40000, 60000, 1000), freq=F) f<- function(x) exp(-(x-5000)^2/18000000)/sqrt(18000000*pi)  x<- seq(40000,

...;green","yellow", "blue")) > filled.contour(volcano, color = Brazilan.Pallete) -- Bernardo Rangel Tura, M.D,MPH,Ph.D National Institute of Cardiology Brazil ------------------------------ Message: 4 Date: Thu, 10 Sep 2009 11:29:58 +0000 (GMT) From: KABELI MEFANE <kabelimefane at yahoo.co.uk> Subject: Re: [R] Help on percentage of random numbers for different classes To: Robert Baer <rbaer at atsu.edu> Cc: R-help at r-project.org Message-ID: <273246.86775.qm at web27803.mail.ukl.yahoo.com> Content-Type: text/plain Dear Robert ? Thank you very muc...

Dear All   I know that you do not have to help me (as this is not a pure R problem) but please do, i am new to R as a CPI compiler, i just need to do a sample to see which sampling method best works in different situations, therefore since this is for practice purposes nobody will finance a real project thats why i need you to help me direct me as to how simulate data (just direct me,not 100%

Dear All   I hope you can help me with this small problem. I want to draw a normal distribution line to this data: p<-rnorm(100, mean=50000, sd=3000) hist(p)   Kabeli [[alternative HTML version deleted]]

R -helpers   i have been trying to do this problem without must success,i managed to do a graph for x, but it is not what i want to define,(i want to specify number of observations as well). I have also been able to do simple rendom sample.   data.frame(ID=c(1,2,3),mu=c(10000,34000,50000),sigma=c(2000,3000,5000)) curve(dnorm(x,mean=parms$mu[1],sd=parms$sigma[1]),from=2000, to=80000,

R-helpers   A curious question: Can you make suggestions  as to  what to use in R for the data from a sample of the following:   Hypermarket <- matrix(rnorm(100, mean=50000, sd=5000)) Supermarket <- matrix(rnorm(400, mean=34000, sd=3000)) Minimarket  <- matrix(rnorm(1000, mean=10000,sd=2000)) Cornershop  <- matrix(rnorm(1500, mean=2500, sd=500)) Spazashop   <- matrix(rnorm(2000,

Hi   Out of curiosity, how can i determine the minimum required sample size of this data in a combined form say 100 entries which r functions can i use?   R helpers   Please help me combine the simulated data to a form of table where: Hypermarket have 10 rows, supermarket have 15 rows,......., spazashops with 35 rows.   Hypermarket <- rnorm(10, mean=20000, sd=7000) Supermarket <-

Dear All   I know that you do not have to help me (as this is not a pure R problem) but please do, i am new to R as a CPI compiler, i just need to do a sample to see which sampling method best works in different situations, therefore since this is for practice purposes nobody will finance a real project thats why i need you to help me direct me as to how simulate data (just direct me,not 100%

Dear Helpers   I have a sample frame and i have sampled from it using three methods and now i want to calculate the statistics but i only get the population parameters.   H <- matrix(rnorm(100, mean=50000, sd=5000)) sampleframe=data.frame(type=c(rep("H",100)),value=c(H)) sampleframe   str=strata(sampleframe,c("type"),size=c(20,), method="srswor")

R-list   I am sorry for asking this stupid question, but i have been running in circles. I want to randomly generate a scaling point of between 1 and 10, for say hundred entries, where the first 10% percent is has rates between 2 and 7, the next 15% 3 and 7, 20% between 3 and 9, 20% between 3 and  10, 35% between 5 and 10. The problem is that i can only generate the usual 100 using runif function