Becky is a UX Researcher and at UserZoom she tailors and analyses projects to clients’ needs. She scopes projects, builds studies, analyses data and delivers insights to clients.
She holds a Masters in Research Methods and a PhD specialising in Decision Making. Before joining UserZoom she worked in a number of different research areas including medical decision making and risk taking. Becky also managed a lab at the Cambridge Judge Business School and lectured in psychology and statistics.
What are confidence intervals and why do we need them in usability studies?
Confidence intervals are calculated from an estimate of how far away our sample mean is from the actual population mean; the amount of error (or discrepancy) from our sample mean to the population mean.
Uncover richer UX insights with automated confidence intervals in UserZoom
We’re excited to announce Confidence Intervals are coming to our all new Results Beta. Easily make informed decisions about your data with the addition of automated confidence intervals for navigation tasks.
Demystifying Statistics: Why and how we adjust the p-value for number of tests run
Continuing our series on Demystifying Statistics, where we answer some of the most common questions we receive about UX stats. In the previous post in the Demystifying Statistics series we discussed what statistical significance means and what a p-value is. In this post we are…
Demystifying Statistics: What is p and what does p < 0.05 mean?
This blog series aims to demystify some of the common questions we get on statistics. In this blog post we will be talking about what a p-value actually is, why does it have to be less than 0.05, and how they can help with making decisions in your UX research.