Then nothing. It simply means the spread is smaller.
The standard deviation (SD) is a measure of spread so small sd = small spread. So the above is true for any distribution, not just the Normal.
Standard Deviation tells you how spread out the set of scores are with respects to the mean. It measures the variability of the data. A small standard deviation implies that the data is close to the mean/average (+ or - a small range); the larger the standard deviation the more dispersed the data is from the mean.
Yes. Standard deviation depends entirely upon the distribution; it is a measure of how spread out it is (ie how far from the mean "on average" the data is): the larger it is the more spread out it is, the smaller the less spread out. If every data point was the mean, the standard deviation would be zero!
I think the answer is variance
A variance is a measure of how far a set of numbers is spread out around its mean.
Because the standard deviation is a measure of the spread in scores. As individuals score more similarly, the spread gets smaller. Because the standard deviation is a measure of the spread in scores. As individuals score more similarly, the spread gets smaller. Because the standard deviation is a measure of the spread in scores. As individuals score more similarly, the spread gets smaller. Because the standard deviation is a measure of the spread in scores. As individuals score more similarly, the spread gets smaller.
It is a measure of how much individual values spread around the average.
Jane Yolen is the writer to the devils arithmetic
The standard deviation and the arithmetic mean measure two different characteristics of a set of data. The standard deviation measures how spread out the data is, whereas the arithmetic mean measures where the data is centered. Because of this, there is no particular relation that must be satisfied because the standard deviation is greater than the mean.Actually, there IS a relationship between the mean and standard deviation. A high (large) standard deviation indicates a wide range of scores = a great deal of variance. Generally speaking, the greater the range of scores, the less representative the mean becomes (if we are using "mean" to indicate "normal"). For example, consider the following example:10 students are given a test that is worth 100 points. Only 1 student gets a 100, 2 students receive a zero, and the remaining 7 students get a score of 50.(Arithmetic mean) = 100 + 0(2) + 7(50) = 100 + 0 + 350 = 450/10 studentsSCORE = 45In statistics, the median refers to the value at the 50% percentile. That means that half of the scores fall below the median & the other half are above the median. Using the example above, the scores are: 0, 0, 50, 50, (50, 50), 50, 50, 50, 100. The median is the score that has the same number of occurrences above it and below it. For an odd number of scores, there is exactly one in the middle, and that would be the median. Using this example, we have an even number of scores, so the "middle 2" scores are averaged for the median value. These "middle" scores are bracketed by parenthesis in the list, and in this case are both equal to 50 (which average to 50, so the median is 50). In this case, the standard deviation of these scores is 26.9, which indicates a fairly wide "spread" of the numbers. For a "normal" distribution, most of the scores should center around the same value (in this case 50, which is also known as the "mode" - or the score that occurs most frequently) & as you move towards the extremes (very high or very low values), there should be fewer scores.
The quadratic mean is a measure of the spread of values about their arithmetic mean. By definition, the arithmetic mean of the differences will be zero and so adds no information. Another measure is required and that is the quadratic mean.
A sports spread is used when bets are being taken on sporting evens. Spread betting gives a gambler the ability to decide if the amount of points given for the spread will be lower or higher than the difference between two team's actual scores.
It is a measure of the spread of the results around their expected value.It is a measure of the spread of the results around their expected value.It is a measure of the spread of the results around their expected value.It is a measure of the spread of the results around their expected value.
The standard deviation (SD) is a measure of spread so small sd = small spread. So the above is true for any distribution, not just the Normal.
Spread It Around - 1970 was released on: USA: 1970
Crush the spread in baseball terminology means to place less distance between the scores of the teams. If a team has 5 and the other team has 8, the team with 5 will want to crush the spread and get at least 4 runs to win the game.
Not spread around
The density will not be as large as one with the same mass which is spread over a smaller volume.