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GNU R：
# Normal Probability Density Function NormalProbabilityDensity <- function(x, myMean, myStdDeviation) { myCoefficient <- 1 / (myStdDeviation * sqrt(2 * pi)) myPower <- -1 * (((x - myMean) ^ 2) / (2 * myStdDeviation ^ 2)) myDensity <- myCoefficient * exp(myPower) myDensity } # Standard Normal Probability Density Function StdNormalProbabilityDensity <- function(x) { myCoefficient <- 1 / (sqrt(2 * pi)) myPower <- -1 * ((x ^ 2) / 2) myDensity <- myCoefficient * exp(myPower) myDensity } ZScore <- function(x, myMean, myStdDeviation) { myZScore <- (x - myMean) / myStdDeviation myZScore } ######################################################################################## myMean <- 15 myStdDeviation <- 3 mySeed <- seq(from=1, to=30, by=1) myProbabilityDensity <- vector(mode="double", length(mySeed)) for (x in c(1:length(mySeed))) { myProbabilityDensity[x] <- NormalProbabilityDensity(mySeed[x], myMean, myStdDeviation) print(sprintf("%2d %.4f", x, myProbabilityDensity[x])) } # plot(main="Normal Probability Distribution", xlab="Seed", ylab="Probability Density", mySeed, myProbabilityDensity) ######################################################################################## mySeed <- seq(from=-1, to=1, by=0.1) myProbabilityDensity <- vector(mode="double", length(mySeed)) for (x in c(1:length(mySeed))) { myProbabilityDensity[x] <- StdNormalProbabilityDensity(mySeed[x]) print(sprintf("%2d %.4f", x, myProbabilityDensity[x])) } plot(main="Standard Normal Probability Distribution", xlab="Seed", ylab="Probability Density", mySeed, myProbabilityDensity)
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