Combination question - Average before same combination repeats

In summary, the total number of possible combinations for the lock is 32. The probability of a randomly generated combination matching the first is 0.015625. On average, you would need to go through 64 combinations before finding a match. The formula for calculating the average number of combinations is 1 / (probability of each value in columns A & B x probability of each value in columns C & D).
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Hi guys, hoping someone can help me with this. I’ve posted this on a couple other forums and so far I haven't had any kind of solid answer on it! I was always better with words than numbers so I have no idea where to begin with this.

So imagine a combination lock with four values in length. The first value is from a choice of two numbers, the second from a choice of two numbers, the third from a choice of four numbers and the fourth from a choice of four numbers.

So it would look like this

?-?-?-? <-- possible combination made
1-1-1-1
2-2-2-2
x-x-3-3
x-x-4-4
--------
a-b-c-dIf a combination was randomly generated, I’m trying to work out on average how many combinations you’d likely go through before one matched the first if 70% of the time the value in column A was the number 1 and 80% of the time the value in column B was the number 1 (the values in column C & D each have a 25% chance). So the odds percentage wise are;

70-80-25-25
30-20-25-25
00-00-25-25
00-00-25-25

I'm also interested in how to work that out so I can change values and percentages and come up with likely averages myself depending on what criteria I’m needing at the time.

Can anyone help and explain how it was worked out so I can learn for myself?
 
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Thanks!

The total number of possible combinations for the lock is 2 x 2 x 4 x 4 = 32. The probability of a randomly generated combination matching the first if 70% of the time the value in column A is the number 1 and 80% of the time the value in column B is the number 1 is (0.7 x 0.8 x 0.25 x 0.25) = 0.015625. This means that on average, you would have to go through 1/0.015625 = 64 combinations before you find one that matches the first.

If you want to be able to change the values and percentages yourself, the formula is:

1 / (probability of each value in columns A & B x probability of each value in columns C & D) = Average number of combinations before finding a match
 

Related to Combination question - Average before same combination repeats

What is a combination question?

A combination question is a type of mathematical problem that involves finding the number of ways to arrange a set of items, taking into account order and repetition.

What is the average before the same combination repeats?

The average before the same combination repeats is the expected number of attempts it will take to see a specific combination of items repeated in a sequence. It is calculated by taking the total number of possible combinations and dividing it by the number of combinations that are unique.

How do you calculate the average before the same combination repeats?

To calculate the average before the same combination repeats, you need to know the total number of possible combinations and the number of unique combinations. The formula is: Average = Total number of combinations / Number of unique combinations.

Why is it important to calculate the average before the same combination repeats?

Calculating the average before the same combination repeats is important because it can help us understand the likelihood of seeing a specific combination repeated in a sequence. This information is useful in various fields such as statistics, probability, and cryptography.

What are some real-life applications of combination questions and calculating the average before the same combination repeats?

Combination questions and calculating the average before the same combination repeats have many real-life applications, including predicting the likelihood of winning in a game of chance, analyzing data in genetics and epidemiology, and determining the security of encryption algorithms. These concepts are also used in various industries, such as finance, manufacturing, and logistics.

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