This difference is statistically significant at p <. The lower boundary of website B’s findability rate (49%) is well above the upper boundary of website A’s findability rate (12%). Black error bars are 90% confidence intervals.Īlmost 60% of 75 participants found the sewing machine on website B compared to only 4% of a different group of 75 participants on website A. For example, Figure 1 shows the findability rates on two websites for different products along with 90% confidence intervals depicted as the black “whisker” error bars.įigure 1: Findability rates for two websites. That is, if there’s no overlap in confidence intervals, the differences are statistically significant at the level of confidence (in most cases). They tell you if two values are statistically different along with the upper and lower bounds of a value. What’s nice about confidence intervals is that they act as a shorthand statistical test, even for people who don’t understand p-values. They are usually 90% or 95% by convention. Confidence intervals visually show the reader the most plausible range of the unknown population average. Confidence Interval Error BarsĬonfidence intervals are one type of error bar that can be placed on graphs to show sampling error. Here are six ways to indicate sampling error and statistical significance to the consumers of your research. Picking the “right” visualization is a balance between knowing your audience, working with conventions in your field, and not overwhelming your reader.

Conveying this concept to a reader is another challenge-especially if a reader is less quantitatively inclined. Understanding and appreciating the consequences of sampling error and statistical significance is one thing. a completion rate, average satisfaction) differs from the actual population average.Ĭonsequently, the differences between designs or attitudes measured in a questionnaire may be the result of random noise rather than an actual difference-what’s referred to as sampling error. It’s rarely possible, or even makes sense, to measure every single person of a population (all customers, all prospects, all homeowners, etc.).īut when you use a sample, the average value you observe (e.g.

Graphpad prism statistical significance