How can I show a rotated PDF plot superimposed on a ListPlot of the underlying data?

Question

I have a set of 3 lifetime datasets in lists called values1, values2 and values3.

values1 = {53377., 16542., 31418., 5629., 17654., 7365., 15797., 862., 76906., 10073.};

values2 = {74412., 15620., 29650., 96951., 9252., 14257., 11684., 84461., 49724., 14903.};

values3 = {69174., 77036., 115837., 105497., 103195., 55433., 90053., 45861., 57840., 33875.};

The plot of this raw data is shown below.

I now use EstimatedDistribution to fit the data to individual Weibull distributions and plot their PDFs.

What I would like to do now is to locate and align the individual PDF curves on top of the raw data plot close to their corresponding data points. The PDFs would be rotated 90 degrees clockwise thereby ending up in a vertical orientation in the final plot. At this point I don’t necessarily need the frames and labels associated with the PDF plots to be included. What is most important is that the Age to Failure axes of the Raw Data plot be aligned with that of the PDF plots so that the resulting composite plot is a true mathematically accurate representation of the information in all 4 plots. Below is a depiction of the formatting I’m after (minus the inclusion of the boxes and whiskers]. I don’t know what software tool created this plot.

The closest I’ve seen to this is in Mathematica is the BoxWhiskerChart but that apparently is unable to show the PDF. Below is my code. Thanks for any help.

values1 = {53377., 16542., 31418., 5629., 17654., 7365., 15797., 862.,
76906., 10073.};

values2 = {74412., 15620., 29650., 96951., 9252., 14257., 11684., 
84461., 49724., 14903.};

values3 = {69174., 77036., 115837., 105497., 103195., 55433., 90053., 
45861., 57840., 33875.};

category1 = Table[1, {10}];
category2 = Table[2, {10}];
category3 = Table[3, {10}];
data1 = Transpose[{category1, values1}];
data2 = Transpose[{category2, values2}];
data3 = Transpose[{category3, values3}];

plot1 = ListPlot[{data1, data2, data3}, Frame -> True, 
PlotRange -> {{0, 4}, {0, 150000}}, 
FrameLabel -> {"Category", "Age to Failure"}, 
FrameTicks -> {{1, 2, 3}, {0, 25000, 50000, 75000, 100000, 125000, 
 150000}, None, None}, PlotLabel -> "Raw Data"]

dist1 = EstimatedDistribution[values1, 
WeibullDistribution[\[Alpha], \[Beta]]]

dist2 = EstimatedDistribution[values2, 
WeibullDistribution[\[Alpha], \[Beta]]]

dist3 = EstimatedDistribution[values3, 
WeibullDistribution[\[Alpha], \[Beta]]]

plotrange = {0, 5*10^-5};

plot2 = Plot[PDF[dist1, t], {t, 0, 75000}, Frame -> True, 
FrameLabel -> {"Age to Failure", "PDF"}, 
PlotLabel -> "Distribution 1 PDF", PlotRange -> plotrange]

plot3 = Plot[PDF[dist2, t], {t, 0, 100000}, Frame -> True, 
FrameLabel -> {"Age to Failure", "PDF"}, 
PlotLabel -> "Distribution 2 PDF", PlotRange -> plotrange]

plot4 = Plot[PDF[dist3, t], {t, 0, 150000}, Frame -> True, 
FrameLabel -> {"Age to Failure", "PDF"}, 
PlotLabel -> "Distribution 3 PDF", PlotRange -> plotrange]

Edit 1: I also looked at DistributionChart which appears to return teardrop-like objects but not the actual PDF (probability density function) plot that I am seeking.

DistributionChart draws a representation of the distribution of values in each Subscript[data, i].

Edit 2: Here is another example showing “vertical PDFs”, this time on a semi-log plot. I believe one of the ReliaSoft products produced this. See here.

Edit 3: Here is George's solution

Answer 1

Here is one somewhat brute force approach:

 dist = {NormalDistribution[.5, .1], BetaDistribution[2, 4]}; 
 peak = First@Maximize[PDF[#, z], z] & /@ dist;
 Show[{ListPlot[{1, #} & /@ RandomVariate[dist[[1]], 50]],
      ListPlot[{2, #} & /@ RandomVariate[dist[[2]], 30]],
      ParametricPlot[{PDF[dist[[1]], x]/peak[[1]]/2 + 1, x }, {x, 0, 1}],
      ParametricPlot[{PDF[dist[[2]], x]/peak[[2]]/2 + 2, x }, {x, 0, 1}]},
      PlotRange -> {{0, 3}, {0, 1}}]

Another way if you want it filled:

 Show[Table[ 
     ListPlot[{k, #} & /@ RandomVariate[dist[[k]], 50]] , {k, 1, 2}], 
  Prolog -> 
     Table[{GrayLevel[.7], 
        Polygon[Table[ {PDF[dist[[k]], x]/peak[[k]]/2 + k, x } , {x, 0, 
           1, .01}]]}, {k, 1, 2}], PlotRange -> {{0, 3}, {0, 1}}]