MATLAB: Convert probability to z-score

z-score

Hi I made the a script is work out the valuse what they should do, but want to make tham in z-score as well can I get a help how to do it please.

Thanks

mu=21; %mean
s=7; %variance what is sqerroot 49
P=normpdf(X,mu,s);
plot(P)
%Probability calculation between 22 and 28 minutes.
PMin=normcdf(22,21,7);
PMax=normcdf(28,21,7);
Prob=PMax-PMin %Probability
%Calculating the probability in 30sec of the mean time.
ApMin=normcdf(20.5,21,7);
ApMax=normcdf(21.5,21,7);
Aprob=ApMax-ApMin

Best Answer

To calculate the z-score from a normal distribution probability, use the norminv (link) function.

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MATLAB: How to go about finding the standard normal probability based on the z-score

doc normcdf
doc normpdf

When you know what you want but not sure the name, try something like

>> lookfor normal
realmin                        - Smallest positive normalized floating point number.
randn                          - Normally distributed pseudorandom numbers.
sprandn                        - Sparse normally distributed random matrix.
surfnorm                       - Surface normals.
isonormals                     - Isosurface normals.
cde                            - cd elliptic function with normalized complex argument.
sne                            - sn elliptic function with normalized complex argument.
addfreqcsmenu                  - Add a cs menu to switch between linear and normalized frequency
convertfrequnits               - converts between Normalized, Hz, kHz, etc
histfit                        - Histogram with superimposed fitted normal density.
jbtest                         - Jarque-Bera hypothesis test of composite normality.
lhsnorm                        - Generate a latin hypercube sample with a normal distribution
logncdf                        - Lognormal cumulative distribution function (cdf).
lognfit                        - Parameter estimates and confidence intervals for lognormal data.
logninv                        - Inverse of the lognormal cumulative distribution function (cdf).
lognlike                       - Negative log-likelihood for the lognormal distribution.
lognpdf                        - Lognormal probability density function (pdf).
lognrnd                        - Random arrays from the lognormal distribution.
lognstat                       - Mean and variance for the lognormal distribution.
mvncdf                         - Multivariate normal cumulative distribution function (cdf).
mvnpdf                         - Multivariate normal probability density function (pdf).
mvnrnd                         - Random vectors from the multivariate normal distribution.
normcdf                        - Normal cumulative distribution function (cdf).
normfit                        - Parameter estimates and confidence intervals for normal data.
norminv                        - Inverse of the normal cumulative distribution function (cdf).
normlike                       - Negative log-likelihood for the normal distribution.
normpdf                        - Normal probability density function (pdf).
normplot                       - Displays a normal probability plot.
normrnd                        - Random arrays from the normal distribution.
normspec                       - Plots normal density between specification limits.
normstat                       - Mean and variance for the normal distribution.
logn3fit                       - Fit a 3-param lognormal dist'n using cumulative probabilities.
wgtnormfit                     - Fitting example for a weighted normal distribution.
wgtnormfit2                    - Fitting example for a weighted normal distribution (log(sigma) parameterization).
>>

Judicious search terms help but seeing the list of things related to "normal" lets you find the two functions of interest (plus a lot more depending upon which toolboxes are available, maybe) that might be of use/interest...

MATLAB: Thresholding data based on z-score

Try this, assuming a 1-D signal:

zScores = zscore(signal)
% Get indexes where zScores > 2
indexes = zScores > 2;
signalWithZMoreThan2 = signal(indexes);

Best Answer

Related Solutions

MATLAB: How to go about finding the standard normal probability based on the z-score

MATLAB: Thresholding data based on z-score

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