Probability

Each time you flip a fair coin it has the same equal chance of landing on heads or tails. That is, even if you get (for example) 19 heads in a row, the next flip still has 50% chance of landing on tails (if the coin is fair).

Standard error

A statistical measure of the dispersion of a set of values. The standard error provides an estimation of the extent to which the mean of a given set of scores drawn from a sample differs from the true mean score of the whole population. It should be applied only to interval-level measures.

Standard deviation

A measure of the dispersion of a set of data from its mean. The more spread apart the data is, the higher the deviation,is defined as follows:

Standard error x sqrt(n) = Standard deviation

Which means that Std Dev is bigger than Std err

Also, Std Dev refers to a bigger sample, while Std err refers to a smaller sample

This is due to Heisenberg's principal of uncertainty.

.30*200*15= 900

.50*320*30= 4,800

.20*410*40= 3,280

Total= 8,980

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Theoretical Probability: P(event) the ratio of the number of favorable outcomes to the number of possible outcomes, written as a ratio.

example: number of favorable outcomes over number of possible outcomes

Amelynn is hungry, so she gets out a bowl and puts in 2 red jelly beans, 3 blue jelly beans, 12 pink jelly beans, and 3 yellow jelly beans. Amelynn likes the pink ones the best. What is the theoretical possibility of her getting a pink jelly bean?

Answer: 12 over 20. (or 3 over 5 [simplest form])

Explanation: Amelynn put 20 jelly beans in the bowl. She wants the pink ones, and there are 12 pink jelly beans, which are the favorable outcomes. There are 20 jelly beans, and these are the possible outcomes. This means that it is 12 over 20. You might have to put this in simplest form as well.

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well first you get in a comfy position and then you slowly put your hand down there trousers, next you rub your hand slowly up and down and if you feel okay with that go abit faster, you might want to rub your clit while doing this.

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A probability distribution is a function that describes the probability of obtaining a certain outcome where the outcomes are not equally likely. There is a fixed probability of getting each outcome, but the probabilities are not necessarily equal. For example, roll 2 dice, there are 36 equally likely outcomes with a probability of each occurring being 1/36. However if we look at the sum of the numbers, there is only one outcome that gives a sum of 2 (1&1) , so P(sum 2) = 1/36, but six outcomes that give the sum of 7 (1&6, 2&5, 3&4, 4&3, 5&2, 6&1), so P(sum 7) = 6/36 = 1/6.

Probability distributions can be tabulated, or there are functions that can be used to calculate the probabilities of getting each outcome.

A probability distribution is a function that describes the probability of obtaining a certain outcome where the outcomes are not equally likely. There is a fixed probability of getting each outcome, but the probabilities are not necessarily equal. For example, roll 2 dice, there are 36 equally likely outcomes with a probability of each occurring being 1/36. However if we look at the sum of the numbers, there is only one outcome that gives a sum of 2 (1&1) , so P(sum 2) = 1/36, but six outcomes that give the sum of 7 (1&6, 2&5, 3&4, 4&3, 5&2, 6&1), so P(sum 7) = 6/36 = 1/6.

Probability distributions can be tabulated, or there are functions that can be used to calculate the probabilities of getting each outcome.

Numbers that are raised to an exponent either increase or decrease at an extremely fast rate.

Homework question? This is actually not a question of probability: if 95% of the parts are non-defective, then 0.95 * 500 = 475 parts are non-defective. So there is zero (0) probability that fewer than 472 parts are non-defective. The question is different when any part has a probability (chance) of 95% of being non-defective. This is a so called Binomial distribution. Google knows the answer.

If it is possible to assume normality, simply convert the desired score to a z-score, and look up the probability for that.

There are 8 corners on a single cube.
There are eight corners on a cube. A cube has six square faces on it and is considered to be a three-dimensional object.

1/4 you see if you flip two coins there's a better chance you'll get a head and a tail then any thing else. 2/4 you'll get a head and a tail, 1/4 you'll get two heads and 1/4 you'll get two tails.

Distinct permutations are the unique permutations of n objects taking r at a time when some of the objects are repeated. For a complete example read below.

First, you need to understand what permutations are. Suppose you have 3 balls, 2 of them blue and one red. Lets call the first blue ball, B1, second blue ball, B2, and the third ball (the red one) R1. Permutation of the three balls taking the three at a time is all the different ways you can arrange those three balls in a row. That number is 3! = 3x2x1 = 6. The arrangements are listed below.

1) B1,B2,R1

2) B1,R1,B2

3) B2,B1,R1

4) B2,R1,B1

5) R1,B1,B2

6) R1,B2,B1

Now, suppose you remove the subscripts. The list looks like this:

1) B,B,R

2) B,R,B

3) B,B,R

4) B,R,B

5) R,B,B

6) R,B,B

Note that you can't differentiate between 1 and 3, they looks like the same. Also, 5 and 6 looks the same, and 2 and 4 looks the same. So the only unique combinations seems to be 1,2 and 5. Those are call the distinct permutations.

To calculate the distinct permutations of n elements taking r at a time use the formula: nPr / (k1!*k2!*...*kn!)

In the example above:

nPr = 3! = 6 -> All permutations of n elements taking r at a time

k1 = 2 = 2 -> because we have two identical blue balls

k2 = 1 = 1 -> we only have one red ball.

So, distinct permutations = 3! / (2!*1!) = 6 /(2*1) = 3. Those distinct permutations are: BBR, BRB, RBB.

You can use a software, such as Wolfram Mathematica, to generate the distinct permutations using the function DistinctPermutations.

(25-21) / (28-20)

= 4/8

=0.5 or 50%

The sum of two random variables that are normally distributed will be also be normally distributed. Use the link and check out the article. It'll save a cut and paste.

A die can have any number of sides; one-sided dice are a joke in the form of a sphere and two-sided dice are often a simple coin shape. Others use platonic solids to give the required number of sides.
The most commonly used are six-sided dice, noted as d6 and usually cubic, but other common numbers include d4 (a tetrahedron), d8 (an octahedron), d10 and d12 (a dodecahedron).

Expressing a probability in terms of a fraction rather than a decimal can give the reader a clearer idea of the chances of an outcome out of all the possible outcomes.

Some examples:

Chance of a coin landing on heads: 1/2 (1 head on a 2-sided coin)

Chance of a dice landing on 4: 1/6 (1 '4' on a 6-sided dice)

Chance of getting an ace in a pack of cards: 4/52 (4 aces in a 52-pack of cards)

== ==

Yes. It is a certain event. If a coin is tossed, a 'head or tail would roll' is a certain event and has probability 1.

There's only one Ace of spades in a 52 card deck so it's 1/52 times the probability of drawing a heart (there are 13 hearts in the same deck, but now there are 51 cards because we already drew one out).

That makes it 1/52 * 13/51 = 13/2652 = 1/204

This is if you want the Ace first, then the heart, if order doesn't matter, you add this to the probability of drawing the heart first, then the Ace of Spades which is (13/52*1/51) =1/204 notice is the same as the first one.

So if order doesn't matter, the probability is 1/204 + 1/204 = 2/204 = 1/102

Let number 1 be: X

number 2 be: Y number 3 be: Z X+Y+Z=98 3X=2Y 8Y=5Z Therefore by substituting you get: 12X=5Z

X+(3/2)X+(12/5)X= 98 10X+15X+24X=980 49X=980; X=20 Then 3(20)=2Y; Y=30 And 12(20)=5Z; Z=48

== == == == 1st number = 20

2nd number = 30

3rd number = 48 Sum of the numbers = 98 1st:2nd = 2:3

2nd:3rd = 5:8 This reallyy doesn't help me!!! ): help, help, help!!!!

with n=15 as fixed, as p=0.5 changes to p=.05 the binmomial distribution will shift to the right.