Number of experiments for a Normal variable.
n = conint_normmunumber ( len , v ) n = conint_normmunumber ( len , v , level )
a 1-by-1 matrix of doubles, positive, the length of the confidence interval.
a 1-by-1 matrix of doubles, the variance
a 1-by-1 matrix of doubles, the confidence level (default level = 1.-0.95=0.05). level is expected to be in the range [0.,0.5]
a 1-by-1 matrix of doubles, integer value, the number of experiments
Returns the number of experiments which guarantees that the
length of the confidence interval is less than len
.
This two-sided confidence interval is for the expectation of the
random variable and we make the assumption that the random
variable has a Normal distribution.
In other words, if x
is a vector
with n
entries, then
[ m, low, up ] = conint_normmu ( x , level , v )
is so that
abs(up-low) <= len
To compute n
, we assume that the random variable
has Normal distribution with known variance v
.
http://en.wikipedia.org/wiki/Confidence_interval
"Introduction to probability and statistics for engineers and scientists", Sheldon Ross, Third Edition, 2004