Probability

There are 36 permutations of two standard dice. Of these, four have a sum of nine, specifically 3+6, 4+5, 5+4, and 6+3. The probability, then, of rolling a nine on a pair of standard dice is 4 in 36, or 1 in 9, or about 0.1111.

It is impossible to determine the percentiles if you are given only the sample mean since percentiles are a measure of the spread of the data; the mean gives no information on that.

The experimental probability of anything cannot be answered without doing it, because that is what experimental probability is - the probability that results from conducting an experiment, a posteri. This is different than theoretical probability, which can be computed a priori. For instance, the theoretical probability of rolling an even number is 3 in 6, or 1 in 2, or 0.5, but the experimental probability changes every time you run the experiment.

A die normally has six sides with the numbers 1 to 6 on them, so any roll will be less than 10 and thus the probability of getting less than 10 with a die is 1.

With two normal dice, the sum of the digits on the dice added together ranges from 2 to 12 and the probability of getting less than 10 is the same as 1 minus the probability of getting 10 or more.

There are 36 ways the two dice can fall and 10 can be achieved in 3 ways (4&6, 5&5, 6&4), 11 can be achieved in 2 ways (5&6, 6&5) and 12 in 1 way (6&6).

Thus the probability of getting 10 or more with 2 dice is (3+2+1)/36 = 6/36 = 1/6

So the probability of getting less than 10 is 1-1/6 = 5/6

The probability of rolling snake eyes on any one throw is 1 in 36. The probability of NOT rolling a snake eyes is 35 in 36. The only outcome here which we do not desire is that in which a non-snake eye roll occurs four times in a row, therefore, we take (35/36)^4 to find the probability of NEVER getting a snake eyes, and then subtract that answer from 1 to get the chances for any outcome WITH at least one pair of snake eyes.

The chances are 10.66% of getting at least one snake eyes in four rolls.

There are 36 permutations of two dice. Of these, 9 have a sum of 5 or 6, so the probability of rolling a sum of 5 or 6 on two dice is 9 in 36, or 1 in 9, or about 0.1111.

The probability of each suit in a standard deck of cards is 13 in 52, or 1 in 4, or 0.25.

It is not explicitly stated in the question, but it is assumed that you draw one marble from each bag. In this case, you have unrelated sequential probability, similar to tossing three coins. The answer is 0.53 or 0.125.

This question cannot be answered. You need the mean and standard deviation in order to compute a Z score for a Raw score. Please restate the question.

8 rocks.

Standard deviation is not a range. It is a single number that represents how much the data is a set of observations varies about the mean. Mathematically it is the square root of the sum of the squares of the differences between the samples and the mean divided by N, or divided by N-1. The decision of N or N-1 depends on whether or not the mean was also calculated with the calculation of the standard deviation. If it was the same calculation, use N-1, it the mean was known beforehand, use N.

For clarification of parenthesis, and use of N or N-1, see the Related Link below.

Rebecca = 7 letters

7!

is

7 * 6 * 5 * 4* 3 * 2

= 5040 different ways

-----------------------------

An ordinary deck of cards has 52 carbs. There are 4 suits in each deck and each suit has 13 cards. You have a 1 in 4 chance of drawing a spade.

Chance of picking first heart card is 13/52, picking second right after is 12/51, total chance is 13/52 multiplied by 12/51. This works if we pick one card, don't replace it and then pick another. Here is the probability of 2 Hearts if we pick two cards at the same time. 13 Hearts choose 2/ 52 cards choose 2= 13C2/52C2=78/1326=1/17

you search in torrents. i found it there.

There are 38 slots on a roulette wheel, two of them being "0" and "00", and the remainders being all numbers from one to thirty-six inclusive.

This means that your chances of getting any number from 1 to 12 are 12/38, or 6/19, which is is just a bit more than 31.5%

5:18

50%

Prob(A given B) = Prob(A and B)/Prob(B)

Neither. Its a 50:50 probability. In the long run, heads will match tails.

Sampling distribution is the probability distribution of a given sample statistic.

For example, the sample mean. We could take many samples of size k and look at the mean of each of those. The means would form a distribution and that distribution has a mean, a variance and standard deviation.

Now the population only has one mean, so we can't do this.

Population distribution can refer to how some quality of the population is distributed among the population.

There are 26*25*24*23*22 = 7,893,600 sets of initials.

i dont know...... it means