You will see on the Ratings Pages we’re showing a lot of data and information. Below is an explanation of the results you see on the page and how they are calculated. For each thing in YouGov Ratings we show nationally representative popularity percentage scores. The positive popularity score shown at the top of the page (on the left) is calculated by taking the proportion of people who view something positively and showing it as a percentage of all of the people who have given any opinion about that thing, including “have heard of”. The same calculation is used for the neutral, negative & have heard of percentage scores. Our sample mirrors the demographics of the US and the data is weighted to be nationally representative. Nice and simple! Below the headline popularity scores you will find more information about the people who view a particular thing positively (aka the fans). For this deeper dive into the fans of a particular thing, we show two different types of results. Wherever you see data (or numbers) on the page, we’re simply showing absolute percentages. For example, for Gender we show the percentage of men and the percentage of women who view that thing positively. For Age, we show the same thing by generation i.e. the percentage of Millennials, Baby Boomers and Generation X who view that thing positively. In this case, Age is defined in generational terms per year of birth: Baby Boomers: 1946-1964 Generation X: 1965-1981 Millenials: 1982-1999 This data in the form of absolute percentages provides a clear breakdown of the people that view a thing positively. We also show other information on the page which, instead of percentages, is in the form of showing what fans of something are more likely to think, like or do. These are correlations. In these instances, instead of looking at fans of something in the form of absolute percentages, we compare the opinions of the fan group with the opinions of the population as a whole to find out what most differentiates them. To do this comparison, we use a statistical method called a Z Score, which helps to highlight what is particularly true of fans compared with another group of people. Crucially, the top Z Score doesn’t necessarily show the majority opinion of the group, but what is most different about the opinions of that group compared to the general population. For example, if we take a group of 1,000 people that like a certain mobile application and see that 20% of them are fans of David Bowie and we take another group of 1,000 people (e.g. a nationally representative group) and find that only 15% of them are fans of David Bowie, in this case, even though just 20% of people that like the mobile application are fans of David Bowie (which isn’t a majority) we are able to see that compared with the rest of the population, the people who like that mobile application are more likely to be fans of David Bowie. The Z score is therefore a very interesting statistical tool used to better understand audiences because it brings to the surface information that particularly differentiates a group that might otherwise be missed, or be difficult to see just looking at absolute percentages or majority proportions.