One (track)
by Alanis Morissette
Year: 1998
From the album Supposed Former Infatuation Junkie (track #11)
Listen on Spotify SPOTIFY
One appears on the following album(s) by Alanis Morissette:
- Supposed Former Infatuation Junkie (track #11) (this album) (1998)
Listen & Collect
Complete your collection or upgrade your listening experience.
Listen to One on YouTube
One ratings
Average Rating = (n ÷ (n + m)) × av + (m ÷ (n + m)) × AVwhere:
av = trimmed mean average rating an item has currently received.
n = number of ratings an item has currently received.
m = minimum number of ratings required for an item to appear in a 'top-rated' chart (currently 10).
AV = the site mean average rating.
Showing latest 5 ratings for this track. | Show all 40 ratings for this track.
| Rating | Date updated | Member | Track ratings | Avg. track rating |
|---|---|---|---|---|
| ! | 06/03/2026 22:24 | wizardalien | 9,736 | 61/100 |
| ! | 05/30/2026 02:12 | Exist-en-ciel | 165,700 | 71/100 |
| ! | 04/11/2026 16:33 | markl73 | 7,030 | 78/100 |
| ! | 01/24/2026 12:51 | 1,630 | 81/100 | |
| ! | 03/07/2025 14:46 | 83,154 | 64/100 |
Rating metrics:
Outliers can be removed when calculating a mean average to dampen the effects of ratings outside the normal distribution. This figure is provided as the trimmed mean. A high standard deviation can be legitimate, but can sometimes indicate 'gaming' is occurring. Consider a simplified example* of an item receiving ratings of 100, 50, & 0. The mean average rating would be 50. However, ratings of 55, 50 & 45 could also result in the same average. The second average might be more trusted because there is more consensus around a particular rating (a lower deviation).
(*In practice, some tracks can have several thousand ratings)
This track has a Bayesian average rating of 76.7/100, a mean average of 75.5/100, and a trimmed mean (excluding outliers) of 76.9/100. The standard deviation for this track is 17.7.
One favourites
Showing all 3 members who have added this track as a favourite
One comments
Be the first to add a comment for this track - add your comment!
