Side Panel

Expand side panel

Table of Contents Module Five 5-2 Discussion: Proper Sampling

5-2 Discussion: Proper Sampling

Listen

View profile card for Chad Armstrong

5-2

Chad Armstrong posted Jul 31, 2025 9:13 PM

This page automatically marks posts as read as you scroll.

Adjust automatic marking as read setting

As the owner of an auto detailing business, I recently ran into an example of improper sampling when I tried to get customer feedback. I asked a few recent customers, ones I personally knew or had good experiences with, to fill out a quick survey about our services. This is an example ofjudgment sampling, where I handpicked individuals based on who I thought would respond positively.

This method is improper because it introduces bias by excluding customers who may have had neutral or negative experiences. As a result, the feedback I received painted an overly positive picture that didn't represent my full customer base. This could lead me to think everything is going great when there might actually be areas needing improvement.

A more accurate approach would have been to use systematic sampling or simple random sampling. For example, I could select every 5th customer from my transaction list or randomly choose a set number of clients from the past month. This would give a more honest and balanced view of my business from a variety of customer perspectives.

This experience showed me how easy it is to accidentally bias results, and how important it is to use proper sampling methods when collecting feedback.

In your response posts, discuss the implications of the improper sampling examples posted by your peers. For example, what sorts of incorrect conclusions could you draw from the investigations? How would you correct the sampling errors in the examples? Try to draw connections to your final project research article: is there any room for improvement of the sampling methodology?

first person response