Black Tie White Noise (track)
by David Bowie
Year: 1993
From the album Black Tie White Noise (track #4)
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Black Tie White Noise appears on the following album(s) by David Bowie:
- Black Tie White Noise (track #4) (this album) (1993)
- The Collaborator - The Legendary Broadcasts (track #49) (compilation) (2016)
- Brilliant Adventure (1992–2001) (track #4) (compilation) (2021)
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Condition: Used
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Black Tie White Noise 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.
| Rating | Date updated | Member | Track ratings | Avg. track rating |
|---|---|---|---|---|
| ! | 12/07/2025 21:10 |  LukasAntoine00s | 5,174 | 80/100 |
| ! | 08/31/2025 02:27 | BurndenAce | 4,304 | 79/100 |
| ! | 03/24/2025 04:37 |  AAL2014 | 35,044 | 76/100 |
| ! | 12/16/2024 23:16 | mjp11 | 9,974 | 84/100 |
| ! | 07/05/2024 05:05 |  PAPPITUFO | 2,782 | 75/100 |
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 74.5/100, a mean average of 74.1/100, and a trimmed mean (excluding outliers) of 74.1/100. The standard deviation for this track is 14.8.
Black Tie White Noise favourites
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Black Tie White Noise comments
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AAL2014 03/24/2025 04:37 | #308171
So strange. Sounds dated yet futuristic all at once.
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