z.test for dataframe

Rui answered the main question by pointing out that you need z.test(m,
stdev=s(m)), or you could use z.test(m,,sd(m)), but I think the stdev=
approach is clearer.  But you are really abusing the concept of z
tests in general (and the z.test function in particular) by using the
sd of the sample.  If you use the sd of the sample then you should be
doing a t test (and the t.test function does this simpler than the
z.test function).  The z.test function was designed to use in classes
that introduce the concepts of inference using the generally
unrealistic (but simpler) case of knowing the population standard
deviation, but not the mean.  The z.test function was to be a bridge
so that the students could use a function that was similar to the
t.test function that they would eventually use.

Hi!
I'm trying to use sapply to my dataframe for z.test function (teaching
demos package)


Sep=cbind(kIp,k02p,k04p,k07p)
Sep=as.data.frame(Sep)

kzt=sapply(Sep, function(m) z.test(m,sd(m)))
Error in z.test(m, sd(Sep)) :
  You must specify a Standard Deviation of the population

kzt=sapply(Sep, function(m) z.test(m,sd(Sep)))
Error in z.test(m, sd(Sep)) :
  You must specify a Standard Deviation of the population

#obviously it can't process the z.test because of the sd function embedded
inside the function. can someone point me how to fix this. Many thanks!

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