What is "central tendency" and "dispersion" and can someone please explain it in laymens terms?
413136
Measures of central tendency are measures of the location of the middle or the center of a distribution. The definition of "middle" or "center" is purposely left somewhat vague so that the term "central tendency" can refer to a wide variety of measures. The mean is the most commonly used measure of central tendency.\n\nWithout knowing something about how data is dispersed, measures of central tendency may be misleading. For example, a residential street with 20 homes on it having a mean value of $200,000 with little variation from the mean would be very different from a street with the same mean home value but with 3 homes having a value of $1 million and the other 17 clustered around $60,000. Measures of dispersion provide a more complete picture. Dispersion measures include the range, average deviation, variance, and standard deviation.
184266
i'm not sure exactly what this means.. usually you want to graph the distribution of some characteristic.  for instance, say you have a group of 1000 people, and you want to show how their heights are distributed.\n\noften the best way to do this is to use a histogram, which shows how many people are a particular height.  often (in the case of height, intelligence, etc) this leads to a bell-shaped distribution.\n\nhere is some more information about histograms:\nhttp://deming.eng.clemson.edu/pub/tutorials/qctools/histm.htm\nhttp://www.anu.edu.au/nceph/surfstat/surfstat-home/1-1-3.html\n\ncheers!
669000
tendency..\nlike ten - dency?
270417
Succinctly, for the normal ditribution, the three averages are equal, that is the mean, median and mode are all the same. Not so in other cases.
1181467
i would say it's a colloid\n\ncolloid="In general, a colloid or colloidal dispersion is a substance with components of one or two phases, a type of mixture intermediate between homogeneous solution and heterogeneous mixture with properties also intermediate between a solution and a mixture."----basically meaning solids suspended in a liquid
633777
Maybe this explanation can help? http://en.wikipedia.org/wiki/Spectral_density
242624
http://en.wikipedia.org/wiki/Mean_%28statistics%29\n\nThis is a link from Wikipedia. It shows lots of examples along with explanations.
719468
c.\n\nIn probability theory and statistics, the coefficient of variation (CV) is a measure of dispersion of a probability distribution. It is defined as the ratio of the standard deviation to the mean
285252
Drift:\nThe physical movement of prohibited substances from the intended target site onto an organic operation or portion thereof.\nwww.ebfarm.com/Organic/Glossary.aspx\n\nDiffusion: # (physics) the process of diffusing; the intermingling of molecules in gases and liquids as a result of random thermal agitation\n# the spread of social institutions (and myths and skills) from one society to another\n# dissemination: the property of being diffused or dispersed\n# dispersion: the act of dispersing or diffusing something; "the dispersion of the troops"; "the diffusion of knowledge"\nwordnet.princeton.edu/perl/webwn\n\nhope this helps!
320722
The central limit theorem still applies.\n\nWhen variables are correlated a principal component analysis will find the independent variables for which the CLT applies.
867547
Try these websites for information on the use of mean, median, and mode in marketing decisions:\n\nhttp://www.learnpremium.co.uk/CIMA/lesson2/page4.aspx\n\nhttp://www.quickmba.com/stats/centralten/\n\nWhat is the appropriate use of mean, median and mode? It's not uncommon to get these three terms confused or misused. In addition, depending on which one is used -- the results can vary widely. So here's an easy way to remember which one is which. "Mean" is average (think mean people as being very average). "Median" is middle (think median strip of a highway) and "Mode" is most common (think "a la mode"). If you were measuring household income, all three measures could give you a different result. Mean income could be the total income divided by the number of households. Median, on the other hand, is that point which half of the people are below and half are above. Mode would be the most common answer. By using different definitions, your answer to "average" income could be $75,000,$56,000 and $45,000 respectively. Bottom line--be careful when you use any one of these terms
400910
"...the variance of a random variable is a measure of its statistical dispersion, indicating how far from the expected value its values typically are."\nhttp://en.wikipedia.org/wiki/Variance\n\nHere are some descriptions of how to calculate it:\nhttp://davidmlane.com/hyperstat/A16252.html\n\nCheers!
29423
Standard deviation tells you how spread out a set of numbers is.  A small standard deviation means that the numbers are close together.  A large one says that they're far apart.\n\nIt's often used as a measure of distance away from the mean.  In a normal distribution, about 68% of numbers are within one standard deviation from the mean.  For example, if you have a normal distribution with a mean of 50 and a standard dev of 10, then about 68% of the numbers are between 40 and 60.  And about 95% of the numbers are within two standard deviations, or between 30 and 70.
935926
It means that there is a large gap in the middle of the data set with one or a small ammount of entries being grossly larger than the majority of the set:\n   the set 1,2,3,4,30 has a mean of 8 and a median of 3\n   the set 20,22,28,32,33,34,64,68,71 has a mean of 49 and \n   a median of 33
810602
The central limit theorem states that given a distribution with a mean μ and variance σ², the sampling distribution of the mean approaches a normal distribution with a mean (μ) and a variance σ²/N as N, the sample size, increases. \n\nThe amazing and counter-intuitive thing about the central limit theorem is that no matter what the shape of the original distribution, the sampling distribution of the mean approaches a normal distribution. \n\nFurthermore, for most distributions, a normal distribution is approached very quickly as N increases. Keep in mind that N is the sample size for each mean and not the number of samples. Remember in a sampling distribution the number of samples is assumed to be infinite.\n\nDEGREE OF FREEDOM:\nThat measure of variability which merely expresses the number of options available within a variable or space. \n\nDegrees of freedom are the equivalent of currency in statistics - you earn a degree of freedom for every data point you collect, and you spend a degree of freedom for each parameter you estimate.
611888
The link below is a pretty good analyzes of the two with out favoring one or the other.  It was written in a method that even I can understand so you should be fine ;-)
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)