Blogs

The Power of Z A common statistical way of standardizing data on one scale so a comparison can take place is using a z-score. The z-score is like a common yard stick for all types of data. Each z-score corresponds to a point in a normal distribution and as such is sometimes called a normal deviate since a z-score will describe how much a point

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Continuous Data Efficiency is one of the cardinal aspects of a product's usability. The amount of time it takes for a user to complete a task is one of the best predictors of efficiency because it: Illustrates the slightest variability (in seconds) that are more difficult to detect in other measures like errors Is a continuous measurement meaning it can be subdivided infinitely (unlike task

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Usability measurements involve human performance and because human behavior is inherently error prone, reaching the goal of 6σ isn't necessary to proclaim success. Manufacturing companies that are considered producing "high-quality" products are usually somewhere between 4σ and 5σ. The benchmarks and targets that we set in our tests will necessarily need to be more forgiving than in manufacturing. I prefer focusing on the movement of

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Minimize Lurking Variables Getting Warmed Up Without task randomization, so-called lurking variables can taint your data--usually not enough that it's devastating but often it's noticeable. One lurking variable when analyzing task times is the user's tendency to perform better on the later tasks and worse on the earlier tasks. It's human nature: someone hands you a piece of paper and says: "Ok, complete the task.

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Six Sigma History and Overview Six Sigma was started in manufacturing for processes that are duplicated thousands and millions of times in something like the placement of a spot weld on sheet metal on a power turbine and being able to predict the failure rate of that part’s weld. If you can measure and control the variability in the manufacturing of this metal, you can

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The benefit of using a z-score in usability metrics was explained in "What's a Z-Score and why use it in Usability Testing?" this article discusses different ways of calculating a z-score. The short answer is: It depends on your data and what you're looking for. If you've encountered the z-score in a statistics book you usually get some formula like: The above formula is for

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The discerning usability analyst should employ a mix of both qualitative and quantitative methods when discovering usability problems. The risks of relying heavily on a qualitative approach can lead to a severe misdiagnosis especially when usability problems are difficult to detect. This article is a response to Nielsen’s "The Risk of Quantitative Studies" and shows how the problems voters had with the “butterfly-ballot” in the

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