Linear Refression-Example 2

nucdat = {{.5,9231},{5.5,8780},{10.5,8191},{15.5,7849},{20.5,7345},{25.5,6997},{30.5,6389},{40.5,5727},{50.5,5151},{60.5,4694}}

{{0.5, 9231}, {5.5, 8780}, {10.5, 8191}, {15.5, 7849}, {20.5, 7345}, {25.5, 6997}, {30.5, 6389}, {40.5, 5727}, {50.5, 5151}, {60.5, 4694}}

ListPlot[nucdat,Prolog→AbsolutePointSize[6],PlotStyle->Hue[.0]]

[Graphics:../HTMLFiles/MATH5_TUT1_457.gif]

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Needs["Statistics`LinearRegression`"]

Fit[nucdat,{1,x},x]

9047.39 - 77.3843 x

regress1 = Regress[nucdat,{1,x},x]

nucdat[[1,2]]

9231

logdat= Table[{nucdat[[i,1]],Evaluate[Log[nucdat[[i,2]]]//N]},{i,1,10}]

{{0.5, 9.13032}, {5.5, 9.08023}, {10.5, 9.01079}, {15.5, 8.96814}, {20.5, 8.90178}, {25.5, 8.85324}, {30.5, 8.76233}, {40.5, 8.65295}, {50.5, 8.54695}, {60.5, 8.45404}}

fig1 = ListPlot[logdat,PlotRange->{8.4,9.2},Frame→True,Prolog→AbsolutePointSize[6],PlotStyle->Hue[.7]]

[Graphics:../HTMLFiles/MATH5_TUT1_463.gif]

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fitnuc=Fit[logdat,{1,x},x]

9.13725 - 0.0115837 x

regress2 = Regress[logdat,{1,x},x]

fig2 = Plot[fitnuc,{x,0,70}]

[Graphics:../HTMLFiles/MATH5_TUT1_467.gif]

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Show[{fig1,fig2}]

[Graphics:../HTMLFiles/MATH5_TUT1_469.gif]

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