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What can you do to get the experimental probability to be closer to the theoretical probability?
The experimental probability is figured out when a person goes through the trouble of actually trying it out. Theoretical probability is when a person comes to a conclusion of what is most likely, based off of the experiment results.
How do theoretical probability and experimental probability relate?
Take for example, flipping a coin. Theoretically, if I flip it, there is a 50% chance that I flip a head and a a 50% chance that I flip a tail. That would lead us to believe that out of 100 flips, there should theoretically be 50 heads and 50 tails. But if you actually try this out, this may not be the case. What you actually get, say 46 heads and 54 tails, is the experimental probability. Thus, experimental probability differs from theoretical probability by the actual results. Where theoretical probability cannot change, experimental probability can.
What is an example of Empirical Probability?
Empirical means by observation, so empirical probability, or experimental probability, is the probability that is observed in a set of trials. For example, if you flip a coin ten times and get seven heads, your empirical probability is 7 in 10. This is different than the theoretical probability, which for a fair coin is 5 in 10, but that result will only be approximated by the empirical results, and then only with a larger number of trials.
What does probability of an event mean?
Probability is the likelihood, expressed in numerical or ratiometric terms, that an event will occur. A probability of 1 means that the event will occur. A probability of 0 means that the event will not occur. A probability of 0.5 means that the likelihood of the event occurring is equal to the likelihood of it not occurring. For instance, a fair coin has a 0.5 probability of being heads, and a 0.5 probability of being tails. Defined formally, probability is the number of permutations of the desired outcome divided by the number of permutations of all possible outcomes. Take a standard six-sided die, for instance. There are six permutations. One of them is a 1, so the probability of rolling a 1 is 1 in 6, or about 0.1667. Probability is not assured. If you roll a die 600 times, you will not necessarily get 100 1's. Over the long run, you will approach that outcome, but each trial will have different results. This is the difference between theoretical probability and experimental probability - theoretical being the mathematical estimate - experimental being the observed results.
How does a large sample size help to ensure that experimental results are reliable?
It made his actual results approach the results predicted by probability
