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Answered 2010-06-20 01:29:54

The probability of 2 coins both landing on heads or both landing on tails is 1/2 because there are 4 possible outcomes. Head, head. Head, tails. Tails, tails. Tails, heads. Tails, heads is different from heads, tails for reasons I am unsure of.

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Since there are 6 possible outcomes, and you want the probability of obtaining one of the outcomes (in your case 6), the probability of it landing on a 6 is 1/6.


There are 6 outcomes, a 2 is one of them so the probability is 1/6.




This question can be rather easily answered, as soon as outcomes 'a' and 'b' are defined.


The favourable outcomes are 1, 3, 5 or 6 so the probability is 4/6 = 2/3


If a coin is tossed 15 times there are 215 or 32768 possible outcomes.


When two fair coins are tossed, you have the following possible outcomes: HH, HT, TH, TT. So, at most implies that you get either i) zero heads or ii) one head. From the possible outcomes we see that 3 times we satisify the outcome. Thus, probability of at most one head is 3/4.


Each coin has two possible outcomes, either Heads or Tails. Then the number of outcomes when all 4 coins are tossed is, 2 x 2 x 2 x 2 = 16.



The probability that a flipped coin has a probability of 0.5 is theoretical in that it assumes the existence of a perfect coin. The same can be said of the probabilities of the spots appearing on a single tossed die which requires the existence of a perfect die. Here's an example. Consider tossing a coin twice to see what comes up. It could be tail, head, or head tail, or tail, tail or head, head. The theoretical probability of two heads is one in four. In general, theoretical probability is the ratio of the number of times a possible outcome can occur in a given event to the number of times that event occurs.


Total number of possible outcomes = 6Number of successful outcomes = 2Probability = 2/6 = 1/3 = [ 33 and 1/3rd ] percent.


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.


5 outcomes if the sequence is ignored. 24 = 16 outcomes in all.


There is 24 or 16 outcomes. There is 4 ways to get heads once (HTTT & THTT & TTHT & TTTH). So, the probability of getting heads only once if a fair coin is tossed 4 times is 4/16 or 1/4.


The total number of outcomes is 2^5 = 32.



75%. There are 3 possible ways of getting at least one tail from 2 tosses from a coin:Tail & Tail orHead & Tail orTail & HeadEach of these individual outcomes has a probability of 25% (e.g. the probability of getting a tail and then another tail is 25%). Adding the possible outcomes together gives you a total of 75%.



I believe there would be 11 possible outcomes!


The theoretical probability of HT or TH when two coins are tossed is 1/2 . (All possible outcomes are HH,TT,HT,TH). This means that when we run the experiment repeatedly we expect to get the desired result 1/2 of the time. Since you intend to toss the coins 40 times, 20 are expected.


Number of possible outcomes of one coin = 2Number of possible outcomes of six coins = 2 x 2 x 2 x 2 x 2 x 2 = 64Number of possible outcomes with six heads = 1Probability of six heads = 1/64Probability of not six heads = at least one tails = 63/64 = 98.4375%


The probability of it is 37.5%. Since there are 16 possible outcomes. calculated by 2 to the power of 4. only 6 gives you the prefered results then it's a simple 6:16 ratio




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