It is 7.062
9 15 15 15 16 (five data) Range = 16 - 9 = 7 Mean = (9 + 15 + 15 + 15 + 16)/5 = 70/5 = 14 So we have: (9 - 14)2 = (-5)2 = 25 (the square of the difference of data value and the mean value) (15 - 14)2 = 12 = 1, 3(1) = 3 (16 - 14)2 = 22 = 4, the sum is 32 The standard deviation = √(32/5) ≈ 2.5
It would be 3*5 = 15.
score of 92
(15/sqroot(9))=5 So it is 5
It is 3.045
Variance = 17.9047619 Standard Deviation = 4.23140188
The range is 12 and the standard deviation is 3.822448314.
3.898717738 is the standard deviation.
The mean absolute deviation is 2
9 15 15 15 16 (five data) Range = 16 - 9 = 7 Mean = (9 + 15 + 15 + 15 + 16)/5 = 70/5 = 14 So we have: (9 - 14)2 = (-5)2 = 25 (the square of the difference of data value and the mean value) (15 - 14)2 = 12 = 1, 3(1) = 3 (16 - 14)2 = 22 = 4, the sum is 32 The standard deviation = √(32/5) ≈ 2.5
A large standard deviation indicates that the distribution is heavily weighted far from the mean. Take the following example: {1,1,1,1,1,19,19,19,19,19} Mean is 10 and StDev = 9.49 Now look at this data set: {5, 6, 7, 8, 9, 11, 12, 13, 14, 15} Mean is still 10, but StDev = 3.5
It would be 3*5 = 15.
It is 15 points.
7.087547766 is the standard deviation for those figures.
Standard deviation is a calculation. It I used in statistical analysis of a group of data to determine the deviation (the difference) between one datum point and the average of the group.For instance, on Stanford-Binet IQ tests, the average (or, mean) score is 100, and the standard deviation is 15. 65% of people will be within a standard deviation of the mean and score between 85 and 115 (100-15 and 100+15), while 95% of people will be within 2 standard deviations (30 points) of the mean -- between 70 and 130.
score of 92
The standard deviation is a number that tells you how scattered the data are centered about the arithmetic mean. The mean tells you nothing about the consistency of the data. The lower standard deviation dataset is less scattered and can be regarded as more consistent.