統計推論：已知母體標準差

GNU R：

######### Statistics.R ########## ############ 統計推論 ############ ZOf2 <- function(myDiff, myStdDeviation1, myMean1, myNumOfSample1, myStdDeviation2, myMean2, myNumOfSample2) { myValue <- myMean1 - myMean2 myMean <- myDiff myStdDevation <- StdDeviationOf2(myStdDeviation1, myNumOfSample1, myStdDeviation2, myNumOfSample2) myZ <- Z(myStdDevation, myMean, myValue) myZ } # 樣本數 > 30 StdDeviationOf2 <- function(myStdDeviation1, myNumOfSample1, myStdDeviation2, myNumOfSample2) { myStdDeviationOf2 <- sqrt((myStdDeviation1 ^ 2) / myNumOfSample1 + (myStdDeviation2 ^ 2) / myNumOfSample2) myStdDeviationOf2 } MarginErrorOfKnownStdDeviationOf2 <- function(myStdDeviationOf2, myConfidenceInterval) { myZ <- GetZ(myConfidenceInterval + (1-myConfidenceInterval)/2) myMarginErrorOfKnownStdDeviationOf2 <- myZ * myStdDeviationOf2 myMarginErrorOfKnownStdDeviationOf2 } # 樣本數 < 30 PooledStdDeviationOf2 <- function(mySampleVariance1, myNumOfSample1, mySampleVariance2, myNumOfSample2) { myPooledVarianceOf2 <- PooledVarianceOf2(mySampleVariance1, myNumOfSample1, mySampleVariance2, myNumOfSample2) myCoefficient <- 1/myNumOfSample1 + 1/myNumOfSample2 myPooledStdDeviationOf2 <- sqrt(myPooledVarianceOf2 * myCoefficient) myPooledStdDeviationOf2 } PooledMarginErrorOf2 <- function(mySampleVariance1, myNumOfSample1, mySampleVariance2, myNumOfSample2, myConfidenceInterval, isSampleSizeSmall) { myT <- GetT(myConfidenceInterval + (1-myConfidenceInterval)/2, myNumOfSample1+myNumOfSample2-2) myStdDeviationOf2 <- PooledStdDeviationOf2(mySampleVariance1, myNumOfSample1, mySampleVariance2, myNumOfSample2) myPooledMarginErrorOf2 <- myT * myStdDeviationOf2 myPooledMarginErrorOf2 }

應用：

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