Regression und Korrelation

<< Statistics`LinearRegression`

data = {{0.055, 90}, {0.091, 97}, {0.138, 107}, {0.167, 124}, {0.182, 
            142}, {0.211, 150}, {0.232, 172}, {0.248, 189}, {0.284, 
            209}, {0.351, 253}};

data // TableForm

tdata = data // Transpose

tdata // TableForm

dplot = ListPlot[data]

func1 = Fit[data, {1, x}, x]

func1Plot = Plot[func1, {x, 0, 0.4}]

func2 = Fit[data, {1, x^2}, x]

func3 = Fit[data, {1, x, x^2}, x]

func3Plot = Plot[func3, {x, 0, 0.4}]

func4 = Fit[data, {1, x, x^2, x^3}, x]

Show[dplot, func1Plot, func3Plot]

xList = tdata[[1]]

yList = tdata[[2]]

<< Statistics`MultiDescriptiveStatistics`

r = Correlation[xList, yList]

xListNew = { 0.9, 1.1, 1.9, 2.0};
yListNew = { 1.0, 2.1, 0.9, 1.9};

Correlation[xListNew, yListNew]