In this episode, I talk about a survey I didn’t plan to analyze—one that popped up the moment I opened Microsoft Word. Microsoft asked for feedback, and well… I had some. I break down the flaws in their opening question, including directional bias, vague wording, and unlabeled scale points. I also reflect on how these design choices impact data quality and what could have been done better. It’s a reminder that even the most common surveys we see in the wild from even the biggest tech giants c...
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In this episode, I talk about a survey I didn’t plan to analyze—one that popped up the moment I opened Microsoft Word. Microsoft asked for feedback, and well… I had some. I break down the flaws in their opening question, including directional bias, vague wording, and unlabeled scale points. I also reflect on how these design choices impact data quality and what could have been done better. It’s a reminder that even the most common surveys we see in the wild from even the biggest tech giants c...
Sample Design - Part 1. Sample Size - or why just over 1000 responses is enough to generalize findings to millions of people!
Total Survey Design
13 minutes
1 year ago
Sample Design - Part 1. Sample Size - or why just over 1000 responses is enough to generalize findings to millions of people!
In this episode of the Total Survey Design Podcast, we explore the fascinating concept of sample size and its impact on survey accuracy. Discover why just about 1000 responses can represent the views of millions, debunking common misconceptions about survey sampling. We'll dive into the key parameters for calculating sample size, such as margin of error, confidence level, predicted variance, and target population size. Learn how a small, well-chosen sample can provide precise and reliable dat...
Total Survey Design
In this episode, I talk about a survey I didn’t plan to analyze—one that popped up the moment I opened Microsoft Word. Microsoft asked for feedback, and well… I had some. I break down the flaws in their opening question, including directional bias, vague wording, and unlabeled scale points. I also reflect on how these design choices impact data quality and what could have been done better. It’s a reminder that even the most common surveys we see in the wild from even the biggest tech giants c...
