Passing data to t.test in loop

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Passing data to t.test in loop

Paul Johnston-2
Dear All

First post so sorry for any breaches of etiquette.
I have a csv containing the results for a series of experiments which record the time taken for various sizes of iterations.

"run_id","size","time"
1,100,1.00
2,200,2.100
3,100,1.100
4,200,2.100
5,200,1.900
6,300,4.00
7,200,2.5
...

I read the data set, extract the results for each "size" and return various statistics.
The only problem is I would like to iterate over the distinct sizes to do a t.test
My code has a section commented #manual t.test but I have no luck with the attempt labelled #attempt to automate t.test
I'm assuming it's my attempt to pass the data as an argument to t.test()

Any pointers gratefully accepted but as I'm a learner hints rather than a solution are preferred.

Cheers Paul

getwd()
setwd("c:/work/R/experiment1")
# read raw experimental data from results file
data <- read.csv("data1.csv", header = TRUE)
data
#create a new dataframe which has space for a record for each unique size of experiment
# this is to collect collated statistics for each experiment

var_list <- c("num_obs", "size_run", "sample_mean","sample_var","std_dev","se")
var_list_length <- length(var_list)
num_experiments <- length(unique(data$size))
# create the dataframe
df = data.frame(matrix(vector(), num_experiments , var_list_length, dimnames=list(c(),var_list)), stringsAsFactors=F)
# it should be empty
df
# insert the experiment size
df$size_run <- unique(data$size)
# now it should have a single column filled
# using
df$size_run
df
# create a vector with the experiment sizes

for (i in df$size_run)
{
# calculate the sample_variance of observations on a particular size
df$sample_var[df$size == i] <- var(subset(data$time, data$size == i))

# calculate the mean of the returned values for all experiments of the same size
df$sample_mean[df$size == i] <- mean(subset(data$time, data$size ==i))

# calculate the number of observations on a particular size
df$num_obs[df$size == i] <- length(subset(data$time, data$size == i))

# calculate the sd of the data
df$std_dev[df$size == i] <- sd(subset(data$time, data$size == i))

# calculate the standard error
df$se[df$size == i] <- sd(subset(data$time, data$size ==i))/sqrt(length(subset(data$time, data$size ==i)))
}

df

#manual t.test
print("t.test for size  = 100")
t.test(subset(data$time, data$size == 100))

print("t.test for size  = 200")
t.test(subset(data$time, data$size == 200))

print("t.test for size  = 300")
t.test(subset(data$time, data$size == 300))

#attempt to automate t.test
for (i in df$size_run)
{
print(i)
a <- subset(data$time, data$size == i)
print(a)
t.test(a)
}

        [[alternative HTML version deleted]]

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Re: Passing data to t.test in loop

PIKAL Petr
Hi

Is this what you want?

by(data$time, list(data$size), function(x) t.test(x))

Petr

> -----Original Message-----
> From: R-help [mailto:[hidden email]] On Behalf Of Paul
> Johnston
> Sent: Tuesday, December 02, 2014 10:17 AM
> To: [hidden email]
> Subject: [R] Passing data to t.test in loop
>
> Dear All
>
> First post so sorry for any breaches of etiquette.
> I have a csv containing the results for a series of experiments which
> record the time taken for various sizes of iterations.
>
> "run_id","size","time"
> 1,100,1.00
> 2,200,2.100
> 3,100,1.100
> 4,200,2.100
> 5,200,1.900
> 6,300,4.00
> 7,200,2.5
> ...
>
> I read the data set, extract the results for each "size" and return
> various statistics.
> The only problem is I would like to iterate over the distinct sizes to
> do a t.test
> My code has a section commented #manual t.test but I have no luck with
> the attempt labelled #attempt to automate t.test
> I'm assuming it's my attempt to pass the data as an argument to
> t.test()
>
> Any pointers gratefully accepted but as I'm a learner hints rather than
> a solution are preferred.
>
> Cheers Paul
>
> getwd()
> setwd("c:/work/R/experiment1")
> # read raw experimental data from results file
> data <- read.csv("data1.csv", header = TRUE)
> data
> #create a new dataframe which has space for a record for each unique
> size of experiment
> # this is to collect collated statistics for each experiment
>
> var_list <- c("num_obs", "size_run",
> "sample_mean","sample_var","std_dev","se")
> var_list_length <- length(var_list)
> num_experiments <- length(unique(data$size))
> # create the dataframe
> df = data.frame(matrix(vector(), num_experiments , var_list_length,
> dimnames=list(c(),var_list)), stringsAsFactors=F)
> # it should be empty
> df
> # insert the experiment size
> df$size_run <- unique(data$size)
> # now it should have a single column filled
> # using
> df$size_run
> df
> # create a vector with the experiment sizes
>
> for (i in df$size_run)
> {
> # calculate the sample_variance of observations on a particular size
> df$sample_var[df$size == i] <- var(subset(data$time, data$size == i))
>
> # calculate the mean of the returned values for all experiments of the
> same size
> df$sample_mean[df$size == i] <- mean(subset(data$time, data$size ==i))
>
> # calculate the number of observations on a particular size
> df$num_obs[df$size == i] <- length(subset(data$time, data$size == i))
>
> # calculate the sd of the data
> df$std_dev[df$size == i] <- sd(subset(data$time, data$size == i))
>
> # calculate the standard error
> df$se[df$size == i] <- sd(subset(data$time, data$size
> ==i))/sqrt(length(subset(data$time, data$size ==i)))
> }
>
> df
>
> #manual t.test
> print("t.test for size  = 100")
> t.test(subset(data$time, data$size == 100))
>
> print("t.test for size  = 200")
> t.test(subset(data$time, data$size == 200))
>
> print("t.test for size  = 300")
> t.test(subset(data$time, data$size == 300))
>
> #attempt to automate t.test
> for (i in df$size_run)
> {
> print(i)
> a <- subset(data$time, data$size == i)
> print(a)
> t.test(a)
> }
>
>       [[alternative HTML version deleted]]
>
> ______________________________________________
> [hidden email] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> and provide commented, minimal, self-contained, reproducible code.

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