They are probabilities: that is, estimates of the likelihood of an event happening.
They are exactly the same
empirical probability is when you actually experiment with it and get data values, and theoretical probability is when you use math to make an educated guess.
Empirical anything is what is observed. Theoretical is a calculation of what things ought to be.
There is no relationship between sequences and probability.
The difference between experimental probability and theoretical probability is that experimental probability is the probability determined in practice. Theoretical probability is the probability that should happen. For example, the theoretical probability of getting any single number on a number cube is one sixth. But maybe you roll it twice and get a four both times. That would be an example of experimental probability.
They are probabilities: that is, estimates of the likelihood of an event happening.
5746
They are exactly the same
empirical probability is when you actually experiment with it and get data values, and theoretical probability is when you use math to make an educated guess.
Empirical anything is what is observed. Theoretical is a calculation of what things ought to be.
There is no relationship between sequences and probability.
mostly, how good your theory is. Remember, experimental values are from reality.
First, it is important to note that it is very unlikely that the experimental and theoretical probabilities will agree exactly. As an extreme example, if you toss a coin an odd number of times, the resulting experimental probability cannot possibly be exactly 1/2. It should be easy to see that this remains true even if the coin is tossed googleplex+1 number of times.A negative difference could be because the number of trials was too small and, with an increased number of trials, the experimental probability would gradually increase towards the theoretical probability.It is also possible that the theoretical model is wrong. You may have assumed that the coin that was being tossed was fair when it was not. Or there were some factors that you failed to take full account of in your theoretical model.Or, of course, it could be a mixture of both.First, it is important to note that it is very unlikely that the experimental and theoretical probabilities will agree exactly. As an extreme example, if you toss a coin an odd number of times, the resulting experimental probability cannot possibly be exactly 1/2. It should be easy to see that this remains true even if the coin is tossed googleplex+1 number of times.A negative difference could be because the number of trials was too small and, with an increased number of trials, the experimental probability would gradually increase towards the theoretical probability.It is also possible that the theoretical model is wrong. You may have assumed that the coin that was being tossed was fair when it was not. Or there were some factors that you failed to take full account of in your theoretical model.Or, of course, it could be a mixture of both.First, it is important to note that it is very unlikely that the experimental and theoretical probabilities will agree exactly. As an extreme example, if you toss a coin an odd number of times, the resulting experimental probability cannot possibly be exactly 1/2. It should be easy to see that this remains true even if the coin is tossed googleplex+1 number of times.A negative difference could be because the number of trials was too small and, with an increased number of trials, the experimental probability would gradually increase towards the theoretical probability.It is also possible that the theoretical model is wrong. You may have assumed that the coin that was being tossed was fair when it was not. Or there were some factors that you failed to take full account of in your theoretical model.Or, of course, it could be a mixture of both.First, it is important to note that it is very unlikely that the experimental and theoretical probabilities will agree exactly. As an extreme example, if you toss a coin an odd number of times, the resulting experimental probability cannot possibly be exactly 1/2. It should be easy to see that this remains true even if the coin is tossed googleplex+1 number of times.A negative difference could be because the number of trials was too small and, with an increased number of trials, the experimental probability would gradually increase towards the theoretical probability.It is also possible that the theoretical model is wrong. You may have assumed that the coin that was being tossed was fair when it was not. Or there were some factors that you failed to take full account of in your theoretical model.Or, of course, it could be a mixture of both.
When theoretical physicists work on equations and don't test their hypothesis, experimental physicists test their hypothesis and verify their conclusion. Usually theoretical physicists work on things like black holes and string-theory when experimental physicists work on Newtonian laws.
Mathematical probability is how many times something is projected to occur, where as experimental probability is how many times it actually occurred. For example, when discussing the probability of a coin landing heads side up... Mathematical probability is 1:2. However, if you actually carryout an experiment flipping the coin 5 times the Experimental probability may be 2:5
What is the symbol for a Probability of success in a binomial trial?