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Probability
The probability of a certain event is a number expressing the likelihood that a specific event will occur, expressed as the ratio of the number of actual occurrences to the number of possible occurrences. In mathematics, it is a measure of how often an event will happen and is the basis of statistics.
14,643 Questions
2/13
52%
How many face cards are in a deck?
12, plus 2 jokers.
There are 54 cards in all, 52 in the regular deck plus the 2 jokers.
there is a 50% chance that the offspring will be tall.
A fair coin is tossed 9 times What is the probability that At least two heads appear?
well, it will have 6 times of the greater chance.
What is the probability of getting 2 girls and 2 boys of 4 children?
It depends. If the order is important, (2 girls then 2 boys): There's a 1/2 chance of any sex, so the probability is 1/16(or 6.25%). But if it's just any order of 2 girls and 2 boys, then it's a different outcome. Consider the following table. The desired outcome is 2 girls, 2 boys in any order. We can just look for 2 girls, and convert to Boolean values of 1 for girl and 0 for boy. Here is the table:
0 0 0 0: 0
0 0 0 1: 1
0 0 1 0: 1
0 0 1 1: 2*
0 1 0 0: 1
0 1 0 1: 2*
0 1 1 0: 2*
0 1 1 1: 3
1 0 0 0: 1
1 0 0 1: 2*
1 0 1 0: 2*
1 0 1 1: 3
1 1 0 0: 2*
1 1 0 1: 3
1 1 1 0: 3
1 1 1 1: 4
Note each row has five numbers. The first four numbers represent the four children, and the fifth number is a sum of these four numbers. Any time the sum equals exactly 2, then the desired outcome (2 out of the four children are girls).
This happens 6 times out of the 16 total possible outcomes, so the probability is 6/16, or 3/8 = 37.5%
How many children is it possible to have at once?
A major problem with multiple births is the survival of the children. In October 2009, the Suleman octuplets (8 children) were born in California and they were still doing well at the age of 5.
with replacement: binominal distribution f(k;n,p) = f(0;5,5/12) without replacement: hypergeometric distribution f(k;N,m,n) = f(0;12,5,5)
Frequency approach for probability?
Well, that's not much of a question. Perhaps you are asking: What is the frequency interpretation of probability? This is called the classical interpretation of probability. Given n independent and identical trials with m occurrences of of a particular outcome, then the probability of this outcome, is equal to the limit of m/n as n goes to infinity. If you are asking: How can probabilities be estimated given data, based on frequency approach? A table is constructed, with intervals, and the number of events in each interval is calculated. The number of events divided by the total number of data is the relative frequency and an estimate of probability for the particular interval.
What is probability of getting all heads if 3 coins are tossed simultaneously?
There is a probability of 0.5 of heads on each coin, so there is a 1/2 * 1/2 *1/2 = 1/8 = 0.125 chance that all coins land heads. You can also express this as a percentage, 12.5% chance. The odds are 1 in 8 that this can happen.
The probability is the same as if you had no history of twins in your family. There is no genetic component with identical twins, it is just something that happens. Fraternal twins occur if a mother "drops" two eggs in one month. Your father being a fraternal twin does not make you "drop" more than one egg in a month and so does not increase your chances of having twins. Your maternal grandfather being a fraternal twin did not effect your mother's ability to drop more than one egg and so did not effect your ability to "drop" more than one egg and so does not increase your ability to have twins.
What does it mean for a sample to have a standard deviation of zero?
It means that there are is no variation from the mean. In other words, all values in your sample are identical.
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What is the probability of having 3 daughters in a row?
it one out 8 1/8 bc
first child 1/2
second child 1/2
third child 1/2
1/2 x 1/2 x 1/2 = 1/8
What is the difference between a probability distribution and sampling distribution?
A sampling distribution function is a probability distribution function. Wikipedia gives this definition: In statistics, a sampling distribution is the probability distribution, under repeated sampling of the population, of a given statistic (a numerical quantity calculated from the data values in a sample). I would add that the sampling distribution is the theoretical pdf that would ultimately result under infinite repeated sampling. A sample is a limited set of values drawn from a population. Suppose I take 5 numbers from a population whose values are described by a pdf, and calculate their average (mean value). Now if I did this many times (let's say a million times, close enough to infinity) , I would have a relative frequency plot of the mean value which will be very close to the theoretical sampling pdf.
If a die is rolled 3 times what is probability getting 4 threes?
there is 0% probability, unless you are some super nerd, and calculate the chance of it splitting the six and you getting two threes in one roll :p
hypergeom. f(1;13,3,1) * f(1;12,5,1)
Three results are desirable and there are nine possible ones. That gives 3/9, aka 1/3, aka 33%
If you were to flip a coin 4 times what is the probability of you getting heads at least 3 times?
The total number of outcomes you could get by flipping a coin 4 times is 2^4 or 16 ways as each coin toss yields two possible outcomes (Heads or Tails) and there are four trials. With that said, you need to find out how many ways there are to get 3 heads or 4 heads. You could use combinations to find this:
n C r = n! / [ r! (n-r)! ]
4 C 3 = 4! / [ 3! (4-3)! ]
4 C 3 = 4! / 3!
4 C 3 = 4 4 C 4 = 4! / [ 4! (4-4)! ]
4 C 4 = 4! / 4!
4 C 4 = 1 The total numbers of ways that one could get at least 3 H heads is equal to five (4 ways to get three heads, and one way to get 4 heads). So the probability of getting at least 3 heads in four tosses is equal to 5/16 or 31.25%.
What are three ways to write ratio?
there are three ways to write ratio's.
- in words. for example lets say 5 to 20
- in fraction from. 5/20
- regular form 5:20
gambling is a good use. It is also used in politics and in predictions in science
First off, how do I calculate the probability that any one event occurs. The answer is equal to: Number of Possible Chances of Success / Total Number of Chances In this case, the number of possible chances of success is one (there is only one 6 of Diamonds in any deck of cards). The total number of chances equal 52 (there are 52 cards to choose from). Therefore the probability of picking a 6 of Diamonds on the first card is 1/52 or .019. In order to calculate the probability that the first card is a 6 of Diamonds AND the second card is a 3 of Hearts, you multiply the two probabilities. Prob. of 1st Card 6D AND 2nd Card 3H = Prob. 1st Card 6D * Prob. 2nd Card 3H We already know the probability of getting a 6 of Diamonds on the first card is 1/52 or .019. To calculate the probability of getting a 3 of Hearts on the second card, it is important to remember that random occurances do not affect the probability of other random occurrances. What I mean is, if I were to draw a 6 of Diamonds from a deck of cards and then replace it, the probability that I would pick a 6 of Diamonds again is the same as it was the first time. Even if I flip a coin 5 times in a row and they all landed on heads, the probability that I would flip another heads is still 50/50. So basically we can ignore what happened on the first draw, and jsut calculate the probability of getting a 3 of Hearts. Again we use our probability formula: Number of Possible Chances of Success / Total Number of Chances In this case, the number of possible chances of success is one (there is only one 3 of Hearts in any deck of cards). The total number of chances equal 52 (THIS ASSUMES THAT WE PUT THE 6 OF DIAMONDS BACK INTO THE DECK AFTER THE FIRST DRAW IF NOT THE NUMBER OF CHANCES IS 51). Therefore the probability of picking a 3 of Hearts on the second card is 1/52 or .019. Multiply the two probabilities together to get the probability of both occurring: 1/52 * 1/52 = 1/2704 = .00037 (or a .037 percent of a chance)
