forecasting for mortality using a logistic regression

Question

I need to know how to do a forecasting for mortality using a logistic regression, can somebody help?

data = {{1., 0.75}, {2., 0.89}, {3., 0.42}, {4., 0.99}, {5., 0.84},
        {6., 0.34}, {7., 0.83}, {8., 0.93}, {9., 0.76}, {10., 0.11}};

nlm = NonlinearModelFit[data, b Exp[m x]/(1 + b Exp[m x]), {b, m}, x]

the data that has been input is fake, i want to know if am doing a forecasting what kind of data should i input?

Answer 1

So while I can't see your data to make sense, in principle this should work:

data = {{1., 0.75}, {2., 0.89}, {3., 0.42}, {4., 0.99}, {5.,0.84}, 
        {6., 0.34}, {7., 0.83}, {8., 0.93}, {9., 0.76}, {10.,0.11}};

lm = LogitModelFit[ data, x, x ];

lm[11]

0.50088