Today I received a Agiltent 34461A Truevolt multimeter from Xtest.at the Austrian Agilent distributor.
I plan to write some articles about this multimeter and especially about features which imho separates it from it's competition.
I am a Hewlett Packard / Agilent fan but I will try hard to be as unbiased as possible,...
A very interesting feature for me is the histogram display. I enjoyed the online demo's about this feature and after unpacking the meter I had to try this feature immeadetly.
If you wanted to measure the deviation of a source before you had to collect data via a serial usb or gpib bus and then create an excel sheet to visualize it. Therefore you would do such a cumbersome task only if you really need statistical data badly.
With the new Agilent 34461A you can watch the deviation instantly by pressing a button.
To test this feature I connected a 5V reference and let the instrument visualize the data.
After some 4500+ measurements you get a nice picture with an expected Gaussian distribution form.
You can also see that the Reference drifts about ±10 uV and that the reference is about 283 uV off (not as bad as it looks).
The reference and meter grosso modo work as expected, since I have not trimmed the reference against a calibrator yet.
The reference I used is based on the Max6350 chip with an ±0.02% initial accuracy, which translates to ±1mV. That considered it is doing great.It is awfully hard to get your hands on a reference which is a match to the precision of a modern 6.5 digit meter, unfortunately.
Beside the histogram which is relatively easy to interpret, the meter also offers to show the cumulative distribution function (in short CDF). The CDF is represented by the green line on the picture above.
The y axis represents the percentage, the x axis the voltage.
So what is the CDF good for ? You can use the CDF to determine what percentage of the data falls between two points. The gradient of the function is also interesting.The first 10% have a considerably smaller gradient than the rest of the function, which means that the negative outliers in that sector are more rare than the other ones.
You can also see f.e. that 10% of the voltages are of in the range of 5.000272 and 5.000279 V.
The position where the function crosses the x axis is the 50% point which in this case is slightly of the origin point on the positive side.
All in all the CDF is a great addition to an already useful statistical feature.
Many thanks go to the Austrian Agilent Distributer Xtest.at for making this test possible.
More mathematical insight on Gaussian Deviaton and the cumulative distribution function can be found here.