Stochastic logistic process

SetDirectory["/Users/takasu/Library/Developer/Xcode/DerivedData/logistic_models-bgcjevlcrpigywgzsjhvyjrvbagx/Build/Products/Development/"]

data = ReadList["data-eq_intv",Real, RecordLists->True];
Length[data]

ListPlot[data[[1]],Joined->True,PlotRange->All]

gSimulation=ListPlot[data,Joined->True,PlotRange->{0,100}]

ListPlot[data,Joined->True,PlotRange->{-1,10}]

dataT = Transpose[data];
Last[dataT]
Count[Last[dataT],0.0]

averageDyna = Map[ Mean, dataT];

gAverage=ListPlot[averageDyna,Joined->True,PlotStyle->RGBColor[1,0,0],PlotRange->All]

Show[gSimulation, gAverage]

varianceDyna = Map[ (#-Mean[#]).(#-Mean[#])&, dataT];

gVariance=ListPlot[varianceDyna,Joined->True,PlotStyle->RGBColor[1,0,0],PlotRange->All]

var = (b1 d2 + b2 d1)/(b2 + d2)^2/.{b1->0.2, b2->0.002, d1->0.1, d2->0}

deq = {n'[t] == r(1-n[t]/k)n[t], n[0]==10}/.{r->0.1, k->50}

sol = NDSolve[ deq,n[t],{t,0,200}]

gAna = Plot[ Evaluate[ n[t]/.sol ],{t,0,200},PlotRange->All, PlotStyle->RGBColor[0,0,1]]

Show[gSimulation, gAverage, gAna]