what is the definiton to standard deviation, without the jargon?
825321
it is the average amount that each sample (or reading number) deviates from the mean (average). It is a measure of how widely the data is scattered away from the mean.\n\nThis is highly simplified, you might want to look on wikipedia for a better explaination. (it involves square roots and other nasty maths)
826326
A greek letter..... it can mean population standard deviation. Not sure of other meanings.
332290
Generally it is the standard deviation, or range of typical answers.  The mean usually is the center of the bars, but not always.
919154
It depends on whether you want the mean number of heads, the total number of heads, etc.\nIf you want the total, multiply the standard deviation by sqrt(n), where you have n tosses.\nIf you want the average, divide by sqrt(n).\n\n(Note, the formula talked about below is for the *margin* of error, not the standard error. And thats only for means.)
109529
The standard deviation tells you how far away something is from the average.  You can do a standard deviation on any set of data, however most people are familiar with the Normal Distribution.
905827
If a random variable has a standard deviation of s and you take N samples, then the standard deviation of the sample mean is s/sqrt(N).\n\nIn your case you assume that the standard deviation of the random variable is close to 50 because you have such a huge number of samples. Now if you turn around and only look at 30 samples then the standard deviation will be\n50/sqrt(30).
280200
If a random sample size of 25 corresponds to a standard deviation of 30, then you can expect a random sample of size 25N to roughly correspond to a standard deviation of 30 / sqrt(N).\n\nIf 99% of the area under the bell curve is between -Z and +Z standard deviations, then you want 30 Z / sqrt(N) to be less than or equal to 0.5.\n\nMaybe a little more because of the variation of the estimated standard deviation from the true standard deviation.\n\nAlso check that the theory and the measurements both suggest it is appropriate to use the normal or Gaussian distribution.
695289
standard deviation of intercept is a quantity related to the precision of the estimated intercept of the fitted line. It can be calculated by the formula:\n\nS_a = (S_b)*(sqrt( (sum(x_j)^2)/m )) \n\nWhere, S_b is standard deviation of slope\n\nS_b = sqrt( ((m*(s_y)^^2) / [m*(sum(x_j)^2) -(sum x_j)^2] )\n\ns_y is the residual standard deviation.\n\na and b are estimated parameters of the line y = a + bx +err.\n\n[Here, by S_b, I mean S with suffix b, Sorry but its a bit difficult to type mathematics with only text.]\nI hope , I answered your question.
387360
The problem is incompletely or improperly described.\n\nEach member of the population has some characteristic value.  The mean is the average of this value taken over the entire population, which, assuming each member is an equal contributor, is M = sum(values)/N, where N is the population.  If each member has the same value, say 515, then mean would be 515 and the standard deviation would be zero.  If each even-numbered member has value 1030, and each odd-number member has value 0, the mean is 515 and the standard deviation is (approximately) 515.\n\nSo, you have provided enough information to solve the problem satisfactorily.
935234
"In probability and statistics, the standard deviation of a probability distribution, random variable, or population or multiset of values is defined as the square root of the variance.\n\nThe standard deviation is measured in the same units as the values of the population. For a population of distances in meters, the standard deviation is also measured in meters, whereas the variance is measured in square meters."\n\n\nIn essence, standard deviation is used for categorizing groups.\nFor example, the average IQ is 100, the standard deviation to the left would be 85, and deviation to the right would be 115. Two left standard deviations would be 60, two right standard deviations would be 130.\nSame applies to SAT scores, statistics, polls, etc.
999718
what was the question?\n\n\nDo you want to know terms like mean, average, mode, standard deviation, etc.?
64438
Let me see if I can answer your question in English. :-)\n\nI'm sure you have an equation in your notes or book that you can just start plugging stuff into.  It probably looks like this:\n\ns = square root of (X - X bar)^2/(n-1)\n\nBut if you want to know why it works, keep reading.\n\nYou have a list of numbers.  First, you need to find the average, or mean, of those numbers, by adding them up and dividing by how many there were.\n\nNow, if you subtract each number from the mean, you get a new list of numbers.  These are the deviation scores, and tell you how far above or below average each number was.  If you add them up, you will get zero, because some of them are positive and some negative.  That's not very interesting, so we square them to make them all positive.  Then we add up all those squared deviation scores.\n\nYou probably got a pretty large number, and not the one we want, yet.  We want the Standard Deviation, which is sort of like the average deviation.  So just like you divide by the number of scores to get the average, you need to divide the sum of the squared deviation scores by something.  Sometimes we divide it by the number of scores, like you would think, but for complicated reasons it works better if you divide by one less than that.  So if you started with 5 numbers, divide by 4 now.  (Be sure to check your notes or your book to see what your teacher said you should divide by.)\n\nWe're still one step away.  The number you should have now is called the Variance.  It is also a measure of how spread out your numbers were, but it's bigger than we want.  Remember how we squared the deviation scores earlier?  Now we need to undo that by taking the square root.  What you get is the Standard Deviation you wanted.
495873
Standard plot of what?  What is the analysis parameter you are interested in measuring?
655920
The standard deviation is the square root of the variance. Now, the variance is the "average squared difference (distance) of each observation from the mean".\n \nLets think about it. You want a measure of how dispersed the data is, right? Well, suppose you have heights for your data and your trying to compare two groups. For example, you want to know if the height´s of New Yorkers vary more or less than the heights of Floridians. You are NOT trying to see which are taller.\n \nSo you can calculate the average height of each group and then see haw far away from this average each individual height is and then calculate the average distance from the average height. If everyone had the same height, the average distance would be ZERO, reflecting that the population´s height is very CONCENTRATED around its average.\n \nBut why do you use the squared difference? Because if you were to calculate the average of "x - average(x)" you would always get zero, so by squaring and taking the square, you always get a positive number (the distance is always positive).\n \nGot it?
682546
Mean = 2.59\nMedian = 3.1\n\nAnswer: 3.1 - 2.59 = 0.51
266644
I've just answered this in your previous question: "Statistics: Variability & SRS Samples of Population?"\n \nIf you look there, you'll find the formula for the s.d. of p_hat. So that increasind n by multiplying it by "m", reduces (devides) sd (or se) by sqrt(m).\n \nFor example, lets say the sd is 0.2 and the sample size is 100. If you increase the sample to 400 (multiply it by 4), the sd is devided by sqrt(4) = 2, i.e., sd = 0.1.
121079
Variance is the square of the standard deviation......usually given the symbol (small case) sigma.\n\nVariance ==> σ^2\n\nFind that symbol. It's common and should be readily seen on the keypad.