Command:
getTChebBound ( |
|
What:
Retrieves the Tchebycheff's confidence interval for an output variable (useful if the distribution associated with the samples is unknown or simply non-normal) with a 95% confidence
Parameters:
value [double precision #] |
The confidence interval about the mean of the variable. It is not necessary in Matlab |
outVar [char*] |
The name of the output variable of interest |
Return:
error_code [int]: 1 if the operation has occurred without errors, 0 if an error has occurred
Examples:interval = getTChebBound('outVar')
this command retrieves in the Matlab variable interval the Tchebycheff's confidence bound about the mean of the output variable outvar with a 95% of confidence.
About the Tchebycheff's bound:
When
the
distribution of a function is unknown (or simply non- normal)
a
non-parametric method based on the Tchebycheff's theorem can be used to
estimate confidence bounds on the mean.
The hypothesis of the test are:
H0: μ = μ0 against H1: μ ≠ μ0
A confidence interval for a mean specifies a range of values within which the unknown population parameter, in this case the mean, may lie.
The width of the confidence interval gives us some idea about the precision of the estimate. The wider is the interval and the less is the precision of the estimate. We interpret the interval calculated at a 95% level as, we are 95% confident that the interval contains the true population mean. We could also say that 95% of all confidence intervals formed in this manner (from different samples of the population) will include the true population mean.
The hypothesis of the test are:
H0: μ = μ0 against H1: μ ≠ μ0
A confidence interval for a mean specifies a range of values within which the unknown population parameter, in this case the mean, may lie.
The width of the confidence interval gives us some idea about the precision of the estimate. The wider is the interval and the less is the precision of the estimate. We interpret the interval calculated at a 95% level as, we are 95% confident that the interval contains the true population mean. We could also say that 95% of all confidence intervals formed in this manner (from different samples of the population) will include the true population mean.