Shopping For Girls (track)
by Tin Machine

Tin Machine II (12 tracks) « Previous track (#8) This track (#9) Next track (#10) »
StatesideShopping For GirlsBig Hurt

Shopping For Girls appears on the following album(s) by Tin Machine:


Upcoming concerts

Oct
29
Wed
21:00
Someoddpilot Records Showcase - Black Cross Hotel (album release) / Blood Lemon / Still Machine (album release)
Empty Bottle, Chicago, United States. United States
Tickets from Ticketmaster Get tickets
 
Oct
30
Thu
19:00
Halloween Mosh Party: Machine Country, Hard To Kill, Haunter Black, Toe 2 Toe & Cellar Door Left Open
Vultures, Colorado Springs, United States. United States
Tickets from Ticketmaster Get tickets
 
Oct
31
Fri
20:00
Florence + The Machine "Everybody Scream" Album Event - Pres. by Amex
Pioneer Works, Brooklyn, United States. United States
Tickets from Ticketmaster Get tickets
 
Discover more upcoming concerts

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Shopping For Girls ratings

Average Rating: 
74/100 (from 11 votes)
  Ratings distributionRatings distribution Average Rating = (n ÷ (n + m)) × av + (m ÷ (n + m)) × AV
where:
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.
Sort ratings
RatingDate updatedMemberTrack ratingsAvg. track rating
 
70/100
 Report rating
12/16/2024 22:42 mjp11  Ratings distributionRatings distribution 9,85684/100
 
80/100
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08/26/2021 17:42 platus  Ratings distributionRatings distribution 31,28276/100
 
75/100
 Report rating
03/12/2018 12:35 jnfbn  Ratings distributionRatings distribution 8,38487/100
 
65/100
 Report rating
02/18/2018 17:15 Sandrof1969  Ratings distributionRatings distribution 7,46172/100
 
65/100
 Report rating
01/09/2017 05:18 Onater  Ratings distributionRatings distribution 9,89385/100

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 73.9/100, a mean average of 71.8/100, and a trimmed mean (excluding outliers) of 71.8/100. The standard deviation for this track is 5.7.

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