Eric,

your data have different values for the abscissa. In those cases I find TemporalData quite handy - this I use in combination with Around:

fn = "Test_Data.xlsx";
sheets = Import[fn, "Data"];
tData = TemporalData[rawData = sheets[[All, 2 ;;, {-2, -1}]]];
stress[strain_] := With[{sld = tData["SliceData", strain]}, Around[Mean[sld], StandardDeviation[sld]]]

With this simple function you already can do things like:

and those values can be plotted:

ListLinePlot[Table[{Around[strain, 0.000001], stress[strain]}, {strain, 0, .65, .05}], IntervalMarkers -> "Bands", PlotRange -> {0, 22}, Epilog -> {Point /@ rawData }, ImageSize -> Large]

The statistics is made of just three values here, and so we see the somewhat strange effect that some data points are outside of the "band". Does that help? Regards -- Henrik

Hi Eric,

Interpolating is probably not a good idea. Here is one way to compute the mean and standard deviation of stress and strain for the three sheets in the Excel file.

(* Import data from the first 3 sheets *)
data = Import["~/Downloads/Test_Data.xlsx", {"Dataset", 1 ;; 3, All, 5 ;; 6}, 
         HeaderLines -> 1]

(* Compute mean and standard deviation of stress and strain *)
meanStddev = #[All, {"Strain", "Stress"}] & /* Normal /* Values /*
              (Through[{Mean, StandardDeviation}[#]] &) /* Transpose /@ data

(*
{{{0.403469, 0.240323}, {10.729, 5.34928}}, 
{{0.344623, 0.192363}, {10.6931, 5.29}}, 
{{0.325966, 0.199726}, {12.3087, 6.00161}}}
*)

Not sure how you want to present the data. Here is one way. The horizontal axis is the dataset number (sheet) and the vertical axis is the mean with error bars corresponding to +/- standard deviation

Apply[Around, meanStddev, {2}] // Transpose // 
  MapThread[
    ListPlot[#1, PlotLabel -> #2, Frame -> True, ImageSize -> 400, 
      PlotRange -> All] &, {#, {"Stress", "Strain"}}] & // 
 Row[#, Spacer[20]] &

Usually for stress and strain they are plotted against each other to estimate Young's modulus (bu fitting a straight line) and yield strength. Mean and standard deviation don'r reveal much.