The statistical equations here are a bit daunting. How accurate do you need the results to be? If you’re going to make multi-million dollar business decisions, then you need better accuracy. But until we do some surveying, we don’t know anything about the variance! So, initially, we employ conservative assumptions about the variance. More variability requires larger samples. What if you got five different responses? You’d probably keep polling. Would you continue polling? Probably not. Imagine you polled your office colleagues, and the first five people gave the same answer. If the responses tend to be very similar, then we don’t need to sample as much to get the same accuracy as we would if the responses range widely. This factor is the hardest to understand. If the critical decisions will focus on the analysis of these segments, then the statistical accuracy needs to be calculated for these smaller segments and not just for the population. Typically, we analyze the data along some demographic segmentations, for example, region, annual sales volume, or support representative. The bigger the population, the smaller the response rate percentage needs to be - but it not linear. The “population” is the group of interest for the survey. Customer Support Services Question Bankįour Factors Determine Survey Statistical Confidence.Survey Design Training Classes - US Government.Supportability & Survey Training Instructor.
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