Fundamental Frequency Analysis

Hey all,
Currently working on an extended experimental investigation for yr 12 about Mersenne’s Law and whether or not it applies to monofilament fishing line.
Other sources have said that the fundamental frequency is the furthermost left peak, however Mersenne’s law predicts that the frequency should be approximately 700Hz higher than the first peak. Ex:

f=1/(2×0.44) √(5.8/(0.544×〖10〗^(-5) ) )=1173.36Hz
However the furthermost left peak states that at this tension and length, the frequency is around 200Hz. There is a peak around 1200Hz which correlates with the frequency suggested by Mersenne’s Law. I was wondering if Audacity generally picks up lower frequencies better than higher frequencies? Or if there is a technological explanation for this phenomena?

Thank you,

Your question is not clear because you have not said which tools in Audacity you are referring to.
Audacity’s tools deal with signal processing and analysis rather than physical phenomena, so to interpret the results in physical terms is a matter for the person performing the analysis.

Some information about some of Audacity’s tools:

Thanks Steve,
Sorry for being too general. I was referring to the “Plot spectrum” tool in regards to frequency.
I feel as though this phenomena has more to do with the microphone experiencing the proximity effect and less to do with the program.
I was just wondering if this phenomena was related to the actual program’s “plot spectrum” setting and if it generally analyses lower frequencies in more depth.
Thank you,

A simplified description of how Plot Spectrum works is that it divides the audio frequency range into lots of narrow frequency bands.
Each frequency band has equal width in Hz.
The number of bands (hence the width of each band) is determined by the “Size” setting. Higher “Size” = more bands = narrower bands.

Example, analyzing a track that has a sample rate of 44100 Hz:

The total frequency range for the track is half the sample rate - that is, the highest possible frequency that can be represented in a track with a sample rate of 44100 Hz, is 22050 Hz (known as the “Nyquist frequency”).
For a “Size” setting of 1024, the frequency range of 0 to 22050 Hz is divided into 512 equal width bands. (Note that the number of bands is half the “Size” setting).
The width of each band will be 22050 / 512 = 43.0664 Hz.
The effect then collects the sounds that fall into each band, and displays how much sound is in that frequency range.

Does that help?