I hope this discussion would help you:

https://www.researchgate.net/post/Can-I-use-random-sampling-in-qualitative-content-analysis

Probability sampling is the thing more related to quantitative data. You need to play with numbers and the challenge is producing representative result.

But the scenario is not same for qualitative research. Although, you can apply probability sampling here too, it is not practical! Purposive sampling allying with your objective works better in case of qualitative data.

Qualitative data is obtained by purposeful and convenience sampling, whereas mathematical, statistical, or computational methods are used to obtain quantitative data :)

You certainly can use probability sampling to produce a sample for qualitative research. The problem is that this kind of sampling usually needs to produce large Ns if you are going to use it for quantitative work, but it is difficult to do qualitative analysis on large samples.

For probability sampling for quantitative data, you have survey weights. (For more complex probability sampling with auxiliary data you can have calibration weights.) If you design your sample so that you have survey weights, can you somehow apply those weights to the qualitative data too? Qualitative data are not my area, but I would assume you normally think of simple random (equal survey weight) probabilities when looking at qualitative data, so remember to "weigh" your qualitative data as you would your quantitative data. That is, if you find some interesting qualitative information, look at the survey weight to see if it might be very prevalent in your population.

Note that my response assumes you have a probability sample for your quantitative data, and that you do your qualitative assessment for each of those members of the population selected. Of course you could have different selection probabilities, say if half of your quantitative data selections were given a qualitative assessment.

You need to define what you mean by qualitative and quantitative before anyone can give a sensible answer. For example, one definition is metric/quantitative versus categorical/qualitative (e.g., Bartholomew et al.'s https://www.amazon.com/Latent-Variable-Models-Factor-Analysis/dp/0470971924/ref=sr_1_2), or see https://www.amazon.com/Analyzing-qualitative-categorical-data-latent-structure/dp/0201025051/ref=sr_1_1 . Others have different definitions, and which definition you are referring to will determine what answers people can sensible give. But, in general, you can extract different types of data.

you can use probability sampling for quantitative data. The purpose of probability sampling mainly related with selecting representative sample and may have the intention to generalize to the larger population where the sample was selected. But in the case of qualitative data, the main objective is to get quality data or information from the person who is claimed to have the knowledge being studied with no intention to generalize the result. In such a case, purposeful or convenience sampling become very essential than probability sampling.

you can use probability sampling for quantitative data. The purpose of probability sampling mainly related with selecting representative sample and may have the intention to generalize to the larger population where the sample was selected. But in the case of qualitative data, the main objective is to get quality data or information from the person who is claimed to have the knowledge being studied with no intention to generalize the result. In such a case, purposeful or convenience sampling become very essential than probability sampling.

Correcto lo que mencionan los colegas en cuanto al muestro probabilístico sobre todo intencional, que es usado en estudios cualitativos