統計基本公式二

GNU R:

# 統計基本公式二 # 單獨使用時，需要引用外部程式檔 # source("Statistics-0.R") CoefficientOfVariation <- function(myStdDevation, myMean) { myCoefficientOfVariation <- 100 * (myStdDevation / myMean) myCoefficientOfVariation } CoefficientOfVariationFromVector <- function(myData, isSample) { myMean <- Mean(myData) myStdDevation <- StdDevation(myData, isSample) myCoefficientOfVariation <- 100 * (myStdDevation / myMean) myCoefficientOfVariation } PearsonProductMomentCorrelationCoefficient <- function(xData, yData) { xStdDeviation <- StdDeviation(xData, TRUE) yStdDeviation <- StdDeviation(yData, TRUE) myPearsonProductMomentCorrelationCoefficient <- SampleCovariance(xData, yData) / (xStdDeviation * yStdDeviation) myPearsonProductMomentCorrelationCoefficient } WeightedMean <- function(myData, myWeight) { myData <- myData * myWeight WeightedMean <- sum(myData) / sum(myWeight) WeightedMean } MeanForGroupedData <- function(myFreqence, myMidPointClass) { myFreqence <- myFreqence * myMidPointClass mySampleMeanForGroupedData <- Mean(myFreqence) mySampleMeanForGroupedData } VarianceForGroupedData <- function(myFreqence, myMidPointClass, isSample) { if (isSample) { myVarianceForGroupedData <- MeanForGroupedData(myFreqence, myMidPointClass) / (length(myFreqence) - 1) } else { myVarianceForGroupedData <- MeanForGroupedData(myFreqence, myMidPointClass) / length(myFreqence) } myVarianceForGroupedData } Frequency <- function(myData) { myFrequency <- summary(factor(myData)) myFrequency }