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I suppose this answer could help you

You need to decide first at what probability you want to "detect" the problem.

This is a nice example to why theoretical knowledge is necessary even for testers.

The simplified version:

  • p is the probability for failure, 1/N in our case

  • then the probability for success is 1-p

  • and the probability to have N successful tries is (1-p)^N

  • so the probability to have N successful tries and and then a failure would be 1-(1-p)^N

  • extracting N and simplifying a bit assuming big enough N gives:

  • −log(1−x1−p)⋅N

(*) "log" is sometimes referred to (for example in calculators) as ln(x), loge(x) or log(x)

I suppose this answer could help you

You need to decide first at what probability you want to "detect" the problem.

This is a nice example to why theoretical knowledge is necessary even for testers.

The simplified version:

  • p is the probability for failure, 1/N in our case

  • then the probability for success is 1-p

  • and the probability to have N successful tries is (1-p)^N

  • so the probability to have N successful tries and and then a failure would be 1-(1-p)^N

  • extracting N and simplifying a bit assuming big enough N gives:

  • −log(1−x)⋅N

(*) "log" is sometimes referred to (for example in calculators) as ln(x), loge(x) or log(x)

I suppose this answer could help you

You need to decide first at what probability you want to "detect" the problem.

This is a nice example to why theoretical knowledge is necessary even for testers.

The simplified version:

  • p is the probability for failure, 1/N in our case

  • then the probability for success is 1-p

  • and the probability to have N successful tries is (1-p)^N

  • so the probability to have N successful tries and and then a failure would be 1-(1-p)^N

  • extracting N and simplifying a bit assuming big enough N gives:

  • −log(1−p)⋅N

(*) "log" is sometimes referred to (for example in calculators) as ln(x), loge(x) or log(x)

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Source Link
Rsf
Rsf
  • 7.1k
  • 1
  • 24
  • 37

I suppose this answer could help you

You need to decide first at what probability you want to "detect" the problem.

This is a nice example to why theoretical knowledge is necessary even for testers.

The simplified version:

  • p is the probability for failure, 1/N in our case

  • then the probability for success is 1-p

  • and the probability to have N successful tries is (1-p)^N

  • so the probability to have N successful tries and and then a failure would be 1-(1-p)^N

  • extracting N and simplifying a bit assuming big enough N gives:

  • −log(1−x)⋅N

(*) "log" is sometimes referred to (for example in calculators) as ln(x), loge(x) or log(x)

I suppose this answer could help you

You need to decide first at what probability you want to "detect" the problem.

This is a nice example to why theoretical knowledge is necessary even for testers.

I suppose this answer could help you

You need to decide first at what probability you want to "detect" the problem.

This is a nice example to why theoretical knowledge is necessary even for testers.

The simplified version:

  • p is the probability for failure, 1/N in our case

  • then the probability for success is 1-p

  • and the probability to have N successful tries is (1-p)^N

  • so the probability to have N successful tries and and then a failure would be 1-(1-p)^N

  • extracting N and simplifying a bit assuming big enough N gives:

  • −log(1−x)⋅N

(*) "log" is sometimes referred to (for example in calculators) as ln(x), loge(x) or log(x)

Source Link
Rsf
Rsf
  • 7.1k
  • 1
  • 24
  • 37

I suppose this answer could help you

You need to decide first at what probability you want to "detect" the problem.

This is a nice example to why theoretical knowledge is necessary even for testers.