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How Do Changes in Standard Deviation Affect Sample Size Estimation?

The standard deviation is the most common way of measuring variability or “dispersion” in data. The more the data is dispersed, the more measures such as the mean will fluctuate from sample to sample. That means higher variability (higher standard deviations) requires larger sample sizes. But exactly how much do standard deviations—whether large or small—impact

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Sample Sizes for Comparing Rating Scale Means

Are customers more satisfied this quarter than last quarter? Do users trust the brand less this year than last year? Did the product changes result in more customers renewing their subscriptions? When UX researchers want to measure attitudes and intentions, they often ask respondents to complete multipoint rating scale items, which are then compared with

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UX and NPS Benchmarks of Hotel Websites (2023)

Planning your next vacation can be both exciting and overwhelming. Most travelers do their research and make reservations for flights, activities, and accommodations online. In particular, hotel websites offer the convenience of browsing, comparing, and booking hotels from anywhere. Hotel bookings and revenue have recovered from the depths of the pandemic. Yet with all this

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Sample Sizes for Comparing Dependent Proportions

Sample size estimation is an important part of study planning. If the sample size is too small, the study will be underpowered, meaning it will be incapable of detecting sufficiently small differences as statistically significant. If the sample size is too large, the study will be inefficient and cost more than necessary. A critical component

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Are People Who Agree to Think Aloud Different?

In an earlier article, we showed that only about 9% of panel participants will eventually complete a study in which they are asked to think aloud. That is, if you need ten usable think-aloud videos, expect to invite around 111 participants. On the surface, this means you’ll need to plan for a lot of people

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Does Thinking Aloud Reduce the Evaluator Effect?

In Think Aloud (TA) testing, participants speak their thoughts while attempting tasks. The process is meant to help researchers identify usability problems and potential fixes. Indeed, in an earlier analysis, we found an increase in problem discovery. Our evaluation of 153 videos, split between TA and non-TA, revealed that evaluators uncovered 36–50% more problems with

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Are 3D Graphs Always Worse Than 2D Graphs?

There are many ways to visually display quantitative information. Excel offers dozens of chart types and color combinations, including those in 3D. But is it good practice to use 3D graphs? Edward Tufte is a famous and vocal critic of using 3D elements or any other decoration in graphs. In his book, Visual Display of

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Classifying Tech Savviness Levels with Technical Activity Checklists

In an earlier article, we demonstrated the validity of measuring tech savviness with technical activity checklists (TAC™) by analyzing the correlation between TAC scores and successful completion rates in four usability studies. The TAC scores significantly correlated with success rates (i.e., people with higher levels of tech savviness tended to complete more tasks). On average,

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How Have UX Job Titles Changed in the Last 15 Years?

What we do on the job can change. Jobs change and job titles change. Sometimes the titles change more than the jobs. For example, what do you call someone who professionally creates software? One analysis shows that the most popular job title associated with this function has evolved from Computer Programmer in the 1980s, to

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Does Removing the Neutral Response Option Affect Rating Behavior?

Many topics about the design of rating scales can provoke strong opinions and heated debates. The arguments include whether or not scales should include a neutral response. Unlike rating scales with an even number of points (e.g., 4, 6, or 10), rating scales with an odd number of points (e.g., 5, 7, or 11) contain

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