Not necessarily. There may not even be a way to work out a theoretical probability. Furthermore, there is always a chance, however small, that the experimental probability is way off.
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.
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.
It is the theory of what might happen, but not actually what happens. In theory, if you spin a coin 100 times, it should come up on heads 50 times, as there is a 1 in 2 chance of you getting heads on each spin. If you actually do spin a coin 100 times, the total of heads is the experimental probability, so what you actually get. That may not be 50. It is likely to be close to 50 though.
I apologize my question should have read what are the characteristics of a standard normal probability distribution? Thank you
There are 6 sides on a die, so the denominator should be 6. The number 3 appears on the dice once, so the fraction probability should be 1/6.
Theoretical probability is what should occur (what you think is going to occur) and experimental probability is what really occurs when you conduct an experiment.
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.
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.
The term "theoretical probability" is used in contrast to the term "experimental probability" to describe what the result of some trial or event should be based on math, versus what it actually is, based on running a simulation or actually performing the task. For example, the theoretical probability that a single standard coin flip results in heads is 1/2. The experimental probability in a single flip would be 1 if it returned heads, or 0 if it returned tails, since the experimental probability only counts what actually happened.
Theoretical probability- what the probability "should be" if all outcomes are equally likely.
Experimental probability is what actually happens in the real world. For example, if you played a game 60 times where you flip a coin and heads scores a point, theoretically you should get 30 points, right? Well, experimental probability is the actual results. In fact, your experimental probability for that game could even be 45 points scored in 60 tries. just remember: theoretical=in a perfect math world; experimental=real world results.
EXPERIMENTAL PROBABILITYExperimental probability refers to the probability of an event occurring when an experiment was conducted.)In such a case, the probability of an event is being determined through an actual experiment. Mathematically,Experimental probability=Number of event occurrencesTotal number of trialsFor example, if a dice is rolled 6000 times and the number '5' occurs 990 times, then the experimental probability that '5' shows up on the dice is 990/6000 = 0.165.On the other hand, theoretical probability is determined by noting all the possible outcomes theoretically, and determining how likely the given outcome is. Mathematically,Theoretical probability=Number of favorable outcomesTotal number of outcomesFor example, the theoretical probability that the number '5' shows up on a dice when rolled is 1/6 = 0.167. This is because of the 6 possible outcomes (dice showing '1', '2', '3', '4', '5', '6'), only 1 outcome (dice showing '5') is favorable.As the number of trials keeps increasing, the experimental probability tends towards the theoretical probability. To see this, the number trials should be sufficiently large in number.Experimental probability is frequently used in research and experiments of social sciences, behavioral sciences, economics and medicine.In cases where the theoretical probability cannot be calculated, we need to rely on experimental probability.For example, to find out how effective a given cure for a pathogen in mice is, we simply take a number of mice with the pathogen and inject our cure.We then find out how many mice were cured and this would give us the experimental probability that a mouse is cured to be the ratio of number of mice cured to the total number of mice tested.In this case, it is not possible to calculate the theoretical probability. We can then extend this experimental probability to all mice.It should be noted that in order for experimental probability to be meaningful in research, the sample size must be sufficiently large.In our above example, if we test our cure on 3 mice and all of these are cured, then the experimental probability that a mouse is cured is 1. However, the sample size is too small to conclude that the cure works in 100% of the cases.R\
The word "experimental" is usually used to describe data that have come from an actual test or experiment. These data are opposite to "theoretical" data, which are only educated guesses at what the data should look like. In statistics, theoretical probability is used a lot. For example, if I flip a coin, in theory, it would land on each side half of the time. Perform some trials, however, and this percentage may be skewed. The experimental data that you collect probably wouldn't exactly match the theoretical probability.
That means that you should roll a die many times, count how often you get the number "2", then divide this by the total number of rolls. If the die is "fair" (no extra weight on one side), you would expect this experimental probability to be somewhere close to the theoretical probability of 1/6, at least, if you roll often enough.
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.
It is the theory of what might happen, but not actually what happens. In theory, if you spin a coin 100 times, it should come up on heads 50 times, as there is a 1 in 2 chance of you getting heads on each spin. If you actually do spin a coin 100 times, the total of heads is the experimental probability, so what you actually get. That may not be 50. It is likely to be close to 50 though.
The experimental probability of rolling a 3 or a 4 on a number cube cannot be stated here, because it depends on the actual results of a set of trials, results which will vary for each set of trials.Roll a die 10 times and see what you get. Do it another 10 times, and you should see different results.The theoretical probability, however, is well known - it is 2 in 6, or 1 in 3, or about 0.3333.