Noun

standard normal random variable (plural standard normal random variables)Category:English lemmas#STANDARDNORMALRANDOMVARIABLECategory:English nouns#STANDARDNORMALRANDOMVARIABLECategory:English countable nouns#STANDARDNORMALRANDOMVARIABLECategory:English multiword terms#STANDARDNORMALRANDOMVARIABLECategory:English entries with incorrect language header#STANDARDNORMALRANDOMVARIABLECategory:Pages with entries#STANDARD%20NORMAL%20RANDOM%20VARIABLECategory:Pages with 1 entry#STANDARD%20NORMAL%20RANDOM%20VARIABLE

1. (probability theoryCategory:en:Probability theory#STANDARDNORMALRANDOMVARIABLE, statisticsCategory:en:Statistics#STANDARDNORMALRANDOMVARIABLE) A random variable whose probability distribution is a standard normal distribution.
   • 2000, George E. Monahan, Management Decision Making: Spreadsheet modeling, analysis, and applications, volume 1, Cambridge University Press, page 405:

     Suppose ${\displaystyle X\sim N(\mu ,\sigma )}$. Then
     ${\displaystyle Z={\frac {x-\mu }{\sigma }}}$
     is a standard normal random variable. In other words, any normal random variable can be standardized by subtracting the mean from the variable and dividing the difference by the standard deviation.

     Category:English terms with quotations#STANDARDNORMALRANDOMVARIABLE

   • 2010, Todd C. Headrick, Statistical Simulation: Power Method Polynomials and Other Transformations‎, Taylor & Francis (CRC Press), page 1:

     This technique is based on a polynomial transformation that proceeds by taking the sum of a linear combination of a standard normal random variable, its square, and its cube.

     Category:English terms with quotations#STANDARDNORMALRANDOMVARIABLE

   • 2016, Maria Dolores Ugarte, Ana F. Militino, Alan T. Arnholt, Probability and Statistics with R, 2nd Edition, Taylor & Francis (CRC Press), page 297,

     A normal random variable with μ = 0 and σ = 1, often denoted Z, is called a standard normal random variable. […] Further, any normal random variable can be converted to a standard normal random variable using (4.25).