can someone explain standard deviation in english plz?
928318
Standard deviation tells how far away a number in a set is from the mean. Like in data where the numbers are 2,4,6,8,10, the mean of this data is 6. So you have to find the difference of each number and the mean, then square each answer and add together(Sum of squared deviations). Divide this answer by the same number you divided the mean by - 1. So in this case you divided the the total of the numbers above by five, so divide the sum of squared deviation/5-1, this gives you the number they call the variance, take the square root of the answer, and you will get the standard deviation.  So, the sum of the squares for this example is 40, by taking the the square root, you get 6.32
114212
First you have to find the mean (average) of the set of numbers. Standard deviation measures how spread out the values in a data set are. To find standard deviation, take the difference of each number in the data set and the mean, square them individually and then add them together. Then divide that by the number of values. And then take the square root of all of that. It's really hard to write that equation in just plain text, but the link shows you what it looks like.\n\nIt's easier to see with an example.\nFind the standard deviation of 45.7, 43.8, 42.6, and 48.1.\n\nThe mean is the sum of all the numbers divided by the amount.\n(45.7+43.8+42.6+48.1)/4= 180.2/4= 45.05\n\nNow find standard deviation, sd:\nsd^2= [(45.7-45.05)^2 + (43.8-45.05)^2 + (42.6-45.05)^2 + (48.1-45.05)^2]/4\n\nsd^2= [(.65)^2 + (-1.25)^2 + (-2.45)^2 + (3.05)^2]/4\n\nsd^2= (.4425 + 1.5625 + 6.0025 + 9.3025)/4\n\nsd^2= 17.29/4=4.3225\n\nsd=sqrt(4.3226)= 2.08
880121
Yes, you need to convert relative standard derivation to standard derivation first. Use relative standard derivation times the mean.\n\nIn the question, I didnt see anything about number of measurements, so there's no way we can tell n. Since we dont know the number of measurements, we cant tell which distribution, Students' T  or normal distribution, we should use. Look into the questions again, with this much info, we cant do nothing here.
40612
Sigma\none sigma is one standard deviation from the mean, etc.
107133
You have all the information you need.\n\nThe Mean is the same as the average. It's just another term for a simple average. So it's $7500\n\nThe standard error of the mean is the standard deviation divided by the square root of the number of samples. So it's just $650 divided by 10, or 65.
221335
Standard deviation of a random variable X is defined as: \nό=√E((X-E(X))2) = √E(X2)-(E(X))2\n(the 2's of course are squares)
605000
The mean describes the average score, the SD describes the shape and range of the normal distribution, or bell curve. \nWith this information, we can say the following:\nAbout 68% of test-takers got between 65% and 73%- a very tight grouping (the area within 1 SD).  Approximately 95% of people got between 61% and 77% (2 SD), and about 98-99% got between 57% and 81% (a range of 3 standard deviations).
20676
It's easiest to understand the equation for the standard deviation by thinking of it as the square root of the variance.  So really, you need to know the  equation for the variance.  However, there are equations for standard deviation that don't take that into account.  Either way, there are fair explainations of the meaning and equations for standard deviation and variance at the sources listed below.  \n\nFor the simplest explaination of equations for standard deviation, read the section titled "Definition and shortcut calculation of standard deviation".[1]
47438
Take each of your values, and then subtract the mean from them.  E.g., 70 - 56 = 14, 60 - 56 = 4, etc.\n\nNow take each of these answers and square it.  Half of the starting numbers will be negative (eg 30 - 56 = -26) but once you square all of these numbers, they should all be positive.\n\nNow you'll have 7 positive numbers. Add them all together and divide the answer by 7.  Finally, take the square root of that value, and that's the standard deviation.\n\nSo 14, 4, -6, 4, 4, 9, and -26\nbecome 196, 16, 36, 16, 16, 81, and 676\nSummed together gives 1037\ndivided by 7 is ~148.14\nSquare-rooted is ~12.2\n\nThe standard deviation is 12.2.\n\nNOTE: the rt11guru answer that follows is based on a technique used in some larger sample sets where 1 is subtracted from the number of entries, ie the sum is divided by 7-1=6 rather than 7.  That is called the *sample standard deviation*, as shown in the link.
714755
A.  Since the values range from 5 to 55, and if we believe that almost all of the values are within 2 sd's of the mean, then that would mean that there are a total of 4 sd's between 5 and 55.  So we can approximate this standard deviation by saying\n\n(55-5)/4 = 12.5\n\nB.  Since you are taking a sample of 400, then the standard error of the mean is 12.5/sqrt(400) = 0.625.  Since the sample size is large, then the sample mean is approximately normal.  To be within 2 units, then you would have to be within mu-2 and mu+2.  So we can standardize.\n\nz = (mu-2-mu)/0.625 = -3.2\nz = mu+2-mu)/0.625 = 3.2\n\nThe area between these two values would then be approximately 0.9986.\n\nC. In this case, our hypothesis test would look like this.\n\nH0: mu = 35\nHA: mu < 35\n\nOur test statistic would be (31.75-35)/0.625 = -5.2\n\nWe would then reject the null hypothesis.  So we would conclude that the scientists are correct.
967643
z score= (n-mean)/standard deviation\nstandard deviation = square root of variance\n\nz score = (50-24)/ 5\n            = 26/5\n            = 5.2\n\nThe z score of the data is 5.2, meaning n is 5.2 standard deviations from the mean.
551009
If you can't answer this, you have no idea what the empirical rule is.\n\nAbout 68% of all values fall within 1 standard deviation of the mean for the normal distribution.
199982
In statistics, the standard error of a measurement, value or quantity is the standard deviation of the process by which it was generated, after adjusting for sample size. In other words the standard error is the standard deviation of the sample mean.\n\nStandard errors provide simple measures of uncertainty in a value and are often used because:\n\n    * If the standard error of several individual quantities is known then the standard error of some function of the quantities can be easily calculated in many cases;\n    * Where the probability distribution of the value is known, they can be used to calculate an exact confidence interval; and\n    * Where the probability distribution is unknown, relationships like Chebyshev's or the Vysochanskiï-Petunin inequality can be used to calculate a conservative confidence interval.
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.
873308
OK - I will try and explain it, but forgive me if I get myself confused...  hehehe\n\nFirst step - make a bell curve.  Put a mark in the center and label that "7 hours" - that's your mean.  Next, put three marks on either side of that middle point - those will be your standard deviation points.  For the points on the right, ADD 5.3 to the mean for the first one, then add 5.3 again for the 2nd, etc...  Points on the left side of the mean have the 5.3 SUBTRACTED.  (Am I still making sense?  lol)\n\nNow - the 68-95-99.7 rule says that 68% of the freshmen will fall into the area between the first line on EITHER side of the mean, 95% between the second lines and 99.7% between the third lines on either side of the mean.\n\nI think you should be able to figure it from there - I hope so...  Right now I am so confused I think I gave myself a headache!  lol\n\nGood luck!
108492
Assuming you are talking about standard deviation...\n\nSigma is the square root of variance.  If you need to add sigma's together, they are added by taking the square room of the sum of squares.
529581
Approximately 95% of the data is within 2 standard deviations of the mean.\nCheck out this website\nhttp://en.wikipedia.org/wiki/Confidence_interval\nand look under the section\n"Confidence Intervals in Measurement"