This command would not take you very far. I assume you meant
statschitest/S/T=1 observedHist ,expectedHist
or some variation thereof.
To understand the P-value I suggest that you try the following experiment:
1. Create a simple distribution:
Make/O/N=200 ggg
SetScale/P x -100,1,"", ggg
ggg=100*exp(-x^2/400)
Display ggg
2. Create a test distribution by copying ggg and adding some noise:
This command would not take you very far. I assume you meant
or some variation thereof.
To understand the P-value I suggest that you try the following experiment:
1. Create a simple distribution:
Make/O/N=200 ggg
SetScale/P x -100,1,"", ggg
ggg=100*exp(-x^2/400)
Display ggg
2. Create a test distribution by copying ggg and adding some noise:
exg=round(exg+enoise(1))
appendTograph exg
3. Run the test:
4. Now increase the noise and test again:
StatsChiTest/T=1/S exg,ggg
You can draw your own conclusions about P as a function of the noise level.
February 8, 2016 at 12:30 pm - Permalink