Probability

The 'standard deviation' in statistics or probability is a measure of how spread out the numbers are. It mathematical terms, it is the square root of the mean of the squared deviations of all the numbers in the data set from the mean of that set.

It is approximately equal to the average deviation from the mean.

If you have a set of values with low standard deviation, it means that in general, most of the values are close to the mean. A high standard deviation means that the values in general, differ a lot from the mean.

The variance is the standard deviation squared. That is to say, the standard deviation is the square root of the variance. To calculate the variance, we simply take each number in the set and subtract it from the mean. Next square that value and do the same for each number in the set. Lastly, take the mean of all the squares. The mean of the squared deviation from the mean is the variance. The square root of the variance is the standard deviation.

If you take the following data series for example, the mean for all of them is '3'.

3, 3, 3, 3, 3, 3 all the values are 3, they're the same as the mean. The standard deviation is zero. This is because the difference from the mean is zero in each case, and after squaring and then taking the mean, the variance is zero. Last, the square root of zero is zero so the standard deviation is zero. Of note is that since you are squaring the deviations from the mean, the variance and hence the standard deviation can never be negative.

1, 3, 3, 3, 3, 5 - most of the values are the same as the mean. This has a low standard deviation. In this case, the standard deviation is very small since most of the difference from the mean are small.

1, 1, 1, 5, 5, 5 - all the values are two higher or two lower than the mean. This series has the highest standard deviation.

18 different combinations.

When a coin is tossed twice there are four possible outcomes, (H,H), (H,T), (T,H) and

(T,T) considering the order in which they appear (first or second). But if we are

talking of combinations of the two individual events, then the order in which they

come out is not considered. So for this case the number of combinations is three:

(H,H), (H,T) and (T,T).

For the case of tossing a die once there are six possible events.

The number of different combinations when tossing a coin twice and a die once is:

3x6 = 18 different combinations.

probablity is anything that occupies space has mass and can be perceived by our senses,by viraf dalal

It is not.

And that is because the mean deviation of ANY variable is 0 and you cannot divide by 0.

It is 20/52 or 5/13.

A single letter.

33.3% equals 1/3.

1/3 of the word 'eel' would be one letter.

The answer depends on the shape of the spinner and the numbers on it.

2

There is no simple answer to the question because the children's genders are not independent events. They depend on the parents' ages and their genes.

However, if you assume that they are independent events then, given that the probability of a boy is approx 0.52, the probability of 3 boys out of 13 is 0.0273.

The value of the distribution for any value of the random variable must be in the range [0, 1].

The sum (or integral) of the probability distribution function over all possible values of the random variable must be 1.

4/221

There are usually 36 number cards although in some decks there are 32 (the 10s are Ts).

1x6 x 1x6 x 1x6

=1x36 x 1x6

=1 in 216

The probability of scoring an exact value for a continuous variable is zero for any value. The probability of scoring 115 (or more) is 15.87%

There is only one set of data so there is only one mean. Therefore there is no standard error of the mean.

0, since night is defined as the period from when the sun sets to when it rises. So even in the polar regions, the probability is zero - by definition.

What is the school ranking according to top publications?

hehe

Discontinue, Stop! IAW; SPE Worksheet Aide (PDF File on Google)

49

Rolling 2 twice in a row in the first two rolls is 1/6*1/6 = 1/36.

But rolling 2 twice eventually is as close to certainty as you can get.

Well what does the spinner look like

The sampling distribution for a statistic is the distribution of the statistic across all possible samples of that specific size which can be drawn from the population.

Mean and standard deviation are not related in any way.