Probability

1 in 2652. The odds of drawing one red king are 1 in 52. The odds of drawing the second are 1 in 51. Multiply 52 by 51, and you get 2652.

1/676

there's 4 suits in one deck of cards.

if j =11, queen =12, and king =13.

that means there will be 6 even numbers card in one suit, and times that by 4, which mean 24. theres 24 cards are even in a regular deck of cards.

In a standard deck of cards, all the spades are black.

it might be 395,652,150,468,457,125,279,456,000,000 chanch to roll a prime number when a monkey appeares at the door

26 of them.

Because there are only 2 outcomes for the flip of a coin, for 5 flips you just need to take (1/2)5, which equals 1/32.

This implies there are 32 different outcomes for the case of tossing a coin 5 times. From these 32 outcomes 5 have exactly 4 heads: THHHH, HTHHH, HHTHH, HHHTH, and HHHHT. So the probability of getting exactly 4 heads when you toss a coin 5 times is:

P(4H,!T) = 5/32 = 0.15625 ≈ 15.6%

It dependes on the genes of the parent if you have no information of the genes of the parent I cannot tell you

(4!)/(2!2!)(1/4)^4=(1/32)

It's difficult to think of a real event to which an exact probability can be assigned. We say that flipping a coin yields 'heads' with probability 1/2 but we do not know that definitely. The only way of assigning a probability in the sense of numbers of heads versus total numbers of flips is by experiment. (Be aware though that there are other interpretations of the word probability.) If I were to flip a coin 500 times and obtained 249 heads then the experimental probability of obtaining a head would be 249/500 or 0.498.

Wherever there is some random (that is, non-determinate) element in the occurrence of an event.

The first step is to determine what the experiment is: rolling a pair of dice, drawing two cards from a deck of playing cards, selecting numbered cards?

no equal answer

Change request

Probability of hitting the bull's-eye on the next random shot after eliminating . . .

- no answer . . . . . 20%

- 1 answer . . . . . . 25%

- 2 answers . . . . . 331/3%

- 3 answers . . . . . 50%

- 4 answers . . . . . 100%

- 5 answers . . . . . zero

Probability of choosing the one correct answer increases significantly from

these figures if you actually know something about the subject.

A die has 6 sides with the numbers 1,2,3,4,5 and 6. Three of those numbers are even. So the probability of rolling an even number is 3 out of 6, or 1 out of 2.

There is a 1/6 chance of rolling a 4 on a fair die, and a 1/2 chance of a fair coin landing heads up. Multiply 1/6 X 1/2. The probability of both happening is 1/12.

The chance is 0.35

Because you can't live with out them not being married to you.

2*(4/52)*(13/52) = 2*(1/13)*(1/4) = 1/26

The triangular, uniform, binomial, Poisson, geometric, exponential and Gaussian distributions are some that can be so defined. In fact, the Poisson and exponential need only the mean.

Since there are only odd & even numbers, the probability is 1/2 or 0.5.

50/50

The area under the pdf between two values is the probability that the random variable lies between those two values.

If you mean the probability that independent events will occur, it is the product of the individual probabilities that they occur. Ex: Probability of picking a red marble from a jar with 4 red and 6 green marbles and picking a black card from a deck of 52.

P(red) = 4/10 = 2/5

P(black card0 = 26/52 = 1/2

P(both) = 2/5 x 1/2 = 1/5