Rome: June 20-22nd
3 Days of Hands-On Training on UX Methods, Metrics and Analysis. Participants receive a User Experience Research Certificate and 2.5 Continuing Education Credits from the University of Denver. [Read More]
Denver: Aug 17-19 2016
3 Days of Hands-On Training on UX Methods, Metrics and Analysis. Participants receive a User Experience Research Certificate and 2.5 Continuing Education Credits from the University of Denver. [Read More]
Jeff Sauro • March 1, 2016
With the proliferation of big data, the number of statistical tests we can perform seems endless. But the number of fluke discoveries we're likely to detect has increased as well. One of the better known methods for managing this false positive rate is the Bonferroni correction, however, it tends to be too conservative and introduces too many false negatives. A better approach that balances both false positives and false negatives is the Benjamini-Hochberg method which is explained with examples in this article.[Read More]
Jeff Sauro • February 23, 2016
In many cases, the judgment from multiple people collected independently and then aggregated, is better than even the best individual judgment. The idea of aggregating results is a powerful methodological tool that can smooth out unusual forecasts, scientific conclusions, and judgments from experts and novices alike. It's the power behind meta-analysis and using the average of several polls to predict the winner of an election. It can also be applied to user and customer research as well.[Read More]
Jeff Sauro • February 16, 2016
For most customer research, you're rarely able to measure the attitudes or behaviors of everyone. Instead you take a sample of your customers and use this sample to make inferences about the rest of your customers. While sampling is efficient and statistically sound, it comes with some risks. Here are five steps to help reduce some of the risks and make sampling your customer more effective.[Read More]
Jeff Sauro • February 9, 2016
Expert reviews aren't' a substitute for usability testing and don't provide metrics for benchmarking. But they are an effective and relatively inexpensive way to uncover the more obvious pain points in the user experience.
Expert reviews are best used when you can't conduct a usability test or in conjunction with insights collected from observing even just a handful of users attempting realistic tasks on a website or application.
The following five steps for conducting an effective expert review aren't going to make you an "expert" in interface evaluation immediately, but if you apply them with enough practice eventually they might![Read More]
Jeff Sauro • February 2, 2016
False positives are a fact of life when trying to separate the signal from the noise in UX research. As the amount of data we use to make decisions increases, the reality of dealing with false positives does too. Two common types of false positives are phantom usability issues and illusory differences.
While we can never completely eliminate false positives, we can minimize them. In UX research this is best done by managing the false positive rate, replicating studies, and triangulating data with complementary methods and multiple evaluators.[Read More]
