# Mathematics Of Correctness : When To Give Up ?

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### #1 petrushkagoogol

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Posted 15 July 2017 - 12:21 AM

Consider an outcome based on 5 sequential decisions :
N=5 (mandatory)

Probability of Success P(x) >= 0.5 / step

0.5, 0.5, 0.5, 0.5, 0.5 Total = 2.50 Person A
0.4, 0.3, 0.4, 0.8, 0.7 Total = 2.60 Person B

Person B takes a hit initially, but gains in the long term.

0.1, 0.1, 0.1, x, y Total = NA Person C

Person C should give up after event 3 because he cannot reach 2.5 (0.5 * 5), even if he perfects outcome 4 and 5. (1/1).

Is giving up not as stupid as it seems ?

P.S. Application could be a sequential manufacturing industry like diamond processing.

Steps are -

• Cutting
• Polishing
• Interim QA  - introduce a micro QA for minimizing time of subsequent steps for non-eligible diamonds
• Bagging
• Setting
• QA

Edited by petrushkagoogol, 15 July 2017 - 12:25 AM.

### #2 Buffy

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Posted 15 July 2017 - 11:45 AM

You may wish to look up "combined probabilities" and "Bayes' Theorem"...

It is, however, true that people rarely know when to "give up" when they really should.

The 50-50-90 rule: anytime you have a 50-50 chance of getting something right, there's a 90% probability you'll get it wrong,

Buffy

### #3 Farming guy

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Posted 12 August 2017 - 07:48 AM

It is, however, true that people rarely know when to "give up" when they really should.

Is this why gambling is addictive to some?

If the weather forecast calls for a 20% chance of showers, it seems there is a 90% chance it will rain on the hay field that is almost ready to bale.

I don't need to gamble because I farm.

### #4 exchemist

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Posted 25 August 2017 - 11:33 AM

Is this why gambling is addictive to some?

If the weather forecast calls for a 20% chance of showers, it seems there is a 90% chance it will rain on the hay field that is almost ready to bale.

I don't need to gamble because I farm.

Just seen this and I am sure it is all too true. Though I suspect we all tend to remember disproportionately those occasions on which a forecast was wrong, rather than the more routine incidences of them being right.