Do independent experiments add to probability?

In summary, when using two independent experiments that are both known to be 70% accurate in predicting the correct outcome, the probability of obtaining the correct result is increased to 91%. This pattern continues with each additional experiment, leading to a higher level of confidence in the predicted outcome. This is supported by the theory that combining multiple independent experiments can increase the overall accuracy of predictions.
  • #1
karamand
6
0
There are two categories of objects, A and B.
From long term observation, experiment 1 is known to be 70% accurate i.e. it predicts type A or B correctly in 70% of cases.
Experiment 2 is totally independent. It uses different methods and different characteristics. It is also known to predict correctly in 70% of cases.
If both experiment 1 and experiment 2 predict type A, what is the probability that it is type A. Does the fact that both experiments predict the same outcome add to my certainty?
 
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  • #2
philpq said:
There are two categories of objects, A and B.
From long term observation, experiment 1 is known to be 70% accurate i.e. it predicts type A or B correctly in 70% of cases.
Experiment 2 is totally independent. It uses different methods and different characteristics. It is also known to predict correctly in 70% of cases.
If both experiment 1 and experiment 2 predict type A, what is the probability that it is type A. Does the fact that both experiments predict the same outcome add to my certainty?

The probability of correct reasult in case of single test is $P = 1 - .3 = .7$... in case of two tests is $P = 1 - (.3)^{2} = .91$... on case of three test is $P= 1 - (.3)^{3}= .973$ and so on...

Kind regards

$\chi$ $\sigma$
 
  • #3
Thanks - that's what I intuitively felt. The additional test added to my confidence. Do you have any reference to the theory behind this?

Regards
Phil
 

Related to Do independent experiments add to probability?

1. What is an independent experiment?

An independent experiment is one in which the outcome of one experiment does not affect the outcome of another. In other words, the events are not dependent on each other.

2. How do independent experiments affect probability?

Independent experiments add to probability by increasing the number of possible outcomes. For example, if you flip a coin twice, there are four possible outcomes (HH, HT, TH, TT), but if you flip two coins simultaneously, there are only two possible outcomes (heads or tails for each coin).

3. Can independent experiments increase the chances of a desired outcome?

Yes, independent experiments can increase the chances of a desired outcome by increasing the number of opportunities for that outcome to occur. However, the probability of the desired outcome will still depend on the individual probabilities of each experiment.

4. Is it possible for independent experiments to decrease the overall probability?

Yes, it is possible for independent experiments to decrease the overall probability if the individual probabilities of each experiment are less than 1. For example, if you roll a die and flip a coin, the probability of rolling a 6 and getting heads is 1/6 * 1/2 = 1/12, which is lower than the probability of getting a 6 on just the die (1/6).

5. Are there any limitations to using independent experiments to calculate probability?

Yes, there are limitations to using independent experiments to calculate probability. One limitation is that the events must truly be independent, meaning that the outcome of one experiment does not affect the outcome of another. Additionally, the outcomes of the experiments must be equally likely and the sample size must be large enough to accurately represent the population.

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