How to calculate a Z-Critical value using Math.Net Numerics for a normal distribution?

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Is there a way, using the Math.NET library to calculate z-critical values for a given confidence level? Most examples I've seen online suggest looking up the values in a table, but I'd like to do it programmatically if possible. I've gone through the docs, but don't see anything specific.










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    Is there a way, using the Math.NET library to calculate z-critical values for a given confidence level? Most examples I've seen online suggest looking up the values in a table, but I'd like to do it programmatically if possible. I've gone through the docs, but don't see anything specific.










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      Is there a way, using the Math.NET library to calculate z-critical values for a given confidence level? Most examples I've seen online suggest looking up the values in a table, but I'd like to do it programmatically if possible. I've gone through the docs, but don't see anything specific.










      share|improve this question














      Is there a way, using the Math.NET library to calculate z-critical values for a given confidence level? Most examples I've seen online suggest looking up the values in a table, but I'd like to do it programmatically if possible. I've gone through the docs, but don't see anything specific.







      .net statistics mathnet






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      asked Dec 31 '18 at 19:14









      Brian VallelungaBrian Vallelunga

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          I see (https://numerics.mathdotnet.com/api/MathNet.Numerics/SpecialFunctions.htm) that Math.Net Numerics includes the Gaussian error function (Erf) and some related functions (complement, inverse, and inverse complement).



          There is a simple relation between the cdf of the normal distribution and erf, namely that the normal (0, 1) cdf = (1/2)*(1 + erf(z/sqrt(2))). From that you can work out critical values and so on.






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            1 Answer
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            1 Answer
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            active

            oldest

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            active

            oldest

            votes









            0














            I see (https://numerics.mathdotnet.com/api/MathNet.Numerics/SpecialFunctions.htm) that Math.Net Numerics includes the Gaussian error function (Erf) and some related functions (complement, inverse, and inverse complement).



            There is a simple relation between the cdf of the normal distribution and erf, namely that the normal (0, 1) cdf = (1/2)*(1 + erf(z/sqrt(2))). From that you can work out critical values and so on.






            share|improve this answer




























              0














              I see (https://numerics.mathdotnet.com/api/MathNet.Numerics/SpecialFunctions.htm) that Math.Net Numerics includes the Gaussian error function (Erf) and some related functions (complement, inverse, and inverse complement).



              There is a simple relation between the cdf of the normal distribution and erf, namely that the normal (0, 1) cdf = (1/2)*(1 + erf(z/sqrt(2))). From that you can work out critical values and so on.






              share|improve this answer


























                0












                0








                0







                I see (https://numerics.mathdotnet.com/api/MathNet.Numerics/SpecialFunctions.htm) that Math.Net Numerics includes the Gaussian error function (Erf) and some related functions (complement, inverse, and inverse complement).



                There is a simple relation between the cdf of the normal distribution and erf, namely that the normal (0, 1) cdf = (1/2)*(1 + erf(z/sqrt(2))). From that you can work out critical values and so on.






                share|improve this answer













                I see (https://numerics.mathdotnet.com/api/MathNet.Numerics/SpecialFunctions.htm) that Math.Net Numerics includes the Gaussian error function (Erf) and some related functions (complement, inverse, and inverse complement).



                There is a simple relation between the cdf of the normal distribution and erf, namely that the normal (0, 1) cdf = (1/2)*(1 + erf(z/sqrt(2))). From that you can work out critical values and so on.







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                answered Jan 1 at 0:19









                Robert DodierRobert Dodier

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