It all depends on how you measure your noise. The traditional method used quite steep high-pass and low-pass filters to define bandwidth, then used a meter preceded by an RMS rectifier to measure the total noise. The implicit assumption being made was that the noise was white (unchanging voltage with frequency).
But we can do much better now. A much more useful measurement is made via the FFT of an oscilloscope. The FFT breaks the frequency range into bins, each defined by a mathematical high-pass and low-pass filter and assumes that the noise between the filters is white. If the bins are narrow (perhaps only 1Hz wide), then the assumption of unchanging amplitude with frequency within the measurement bandwidth remains appropriate even for 1/f noise (-10dB/decade slope). Thus, the FFT is the ideal way to characterise noise.
But! Oscilloscopes rarely contain an anti-alias filter. Worse, with 20MHz of minimum bandwidth, they see a lot of noise, whereas we are often only concerned with 10kHz and below. So my filters are designed to remove the high frequency noise we're not interested in so that we can wind in oscilloscope gain and use the FFT to measure what we are interested in without overloading the front end.
As pointed out, although an LC filter has a slope of 40dB/decade, it is has a resonance before entering that final slope that must be correctly damped. We want Q = 0.7 for a maximally flat response. And that's the only critical thing, but it's easily set by adding the right resistance to the inductor. That's why my filters have an additional series resistance.
What isn't immediately obvious is that the inductor has shunt capacitance and your deliberate capacitor has series inductance. Both of those parasitic components mean that the 40dB/decade slope does not continue for ever. Fortunately, you have to try quite hard to make a 36mH inductor that has enough shunt capacitance to be a problem. Likewise, you'd need extremely long wires on your deliberate capacitor to cause a problem. If you do a SPICE analysis of my circuits (which include the measured parasitic compoonents) you'll see that they're (deliberately) quite well behaved.
Once we've added our input filter, we no longer need to worry about overloading the oscilloscope. But oscilloscopes sell by bandwidth and small low capacitance devices have plenty of 1/f noise. So we need a low noise pre-amplifier having at least x100 gain to ensure that any 1/f noise we measure is actually from the device we're trying to measure, not the oscilloscope itself. I use an OPA1641 configured as a non-inverting amplifier having A = 100 after the LC filter. That does for most work, but it is perfectly possible to do better using discrete FETs connected in parallel and driving an NE5532A to get noise down to 1nV/root Hz.
Finally, once we've got an FFT on the oscilloscope, it is ragged. We need to average FFTs together to smooth the noise spectrum. Averaging FFTs together seems to be reserved for the more expensive oscilloscopes. If you average 100 FFTs together, the deviations from a fitted curve will be about 0.6dB, which is why I earlier commented about 1dB for noise. Having averaged 100 FFTs together, we export the FFT data as a csv file to a spreadsheet and plot it again (logarithmic frequency axis). Having the raw data available, we can now fit a line to the white noise and characterise that. We can fit a -10dB/decade slope to the 1/f noise and characterise that. Usually, I find that there's also -20dB/decade noise due to thermal dependencies, so that's also needed. It all sounds complicated (and it is), but having fitted in this way and defined what the noise is, you can try reducing it and see whether you have actually made a difference. The -20dB/decade thermal dependency noise is the easiest to tackle and is usually reduced by adding thermal insulation around semiconductors and shielding them from draughts (just like the voltage reference data sheets tell you to do).
As Lord Kelvin observed, once you have some proper numbers, you have proper knowledge and you can advance. The old-fashioned single figure noise measurements aren't really much use. Here's an example of what I measured via one of my filters: