The standard deviation of the scores 100 92 94 95 81 82 87 89 71 71 73 61 62 68 51 55 is: 15.1921
For 51 10 19 32 23 47 67: σ=20.2308
n probability theory and statistics, thestandard deviation of a statistical population, a data set, or a probability distribution is the square root of itsvariance. Standard deviation is a widely used measure of the variability ordispersion, being algebraically more tractable though practically less robustthan the expected deviation or average absolute deviation.It shows how much variation there is from the "average" (mean). A low standard deviation indicates that the data points tend to be very close to the mean, whereas high standard deviation indicates that the data are spread out over a large range of values.For example, the average height for adult men in the United States is about 70 inches (178 cm), with a standard deviation of around 3 in (8 cm). This means that most men (about 68 percent, assuming a normal distribution) have a height within 3 in (8 cm) of the mean (67-73 in (170-185 cm)) - one standard deviation, whereas almost all men (about 95%) have a height within 6 in (15 cm) of the mean (64-76 in (163-193 cm)) - 2 standard deviations. If the standard deviation were zero, then all men would be exactly 70 in (178 cm) high. If the standard deviation were 20 in (51 cm), then men would have much more variable heights, with a typical range of about 50 to 90 in (127 to 229 cm). Three standard deviations account for 99.7% of the sample population being studied, assuming the distribution is normal (bell-shaped).
Standard Deviation Explained:Standard deviation is a simple measure of width of a distribution of numbers (usually scores or measurements). It is the next high degree of sophistication of characterizing a bunch of number other than just giving the average ( or mean, median, mode). If you know the average, you do not know how tightly the numbers are clustered around the average, that is what the standard deviation tells you. It is one definition, the most common definition, of the width of a distribution. (There are, of course, many other additional characterizations.)It is important because it tells you if the average is a very useful quantity to use to interpret the data. If someone tells you that the average person your age dies in 50 years, that seems important, but if someone says that the average person dies in 50 years, give or take 20 years, suddenly you realize there is more to the story and maybe you should save more money, just in case. Well, the "give or take" part of that statement is very useful, but not well defined. If they say the life expectancy is 50 years with a standard deviation of 20 years, then that is perfectly defined mathematically. Standard deviation is a mathematical measure of the broadness of the distribution of data.The following two data sets, A and B, have the same mean (average):A: 48, 49, 50, 51, 52B: 30, 40, 50, 60, 70The distribution of the data about the mean in A is very narrow, whereas the distribution about the mean in B is broad. The S.D. gives us a quantification of the broadness of the distribution.In normal distributions, about 68 percent of the data will fall within one S.D. on either side of the mean. About 96 percent of the data will fall with two S.D.Let's say your teacher gives a test to one hundred kids and the test average is 80 points and the S.D. is 10. If the distribution is "normal," about 34 kids will score between 70 and 80, and about 34 kids will score between 80 and 90. We can also predict that about 14 kids will score between 90 and 100, and 14 will score below 70. That leaves four kids. They fall into two groups: they either totally bombed the test, or they got the extra credit question to boost their score over 100!
z = (x - mean_x)/standard_deviation → z = (51 - 57)/3.5 = -1.71 Being negative, it shows it is less than the mean; only the absolute value needs to be considered Looking up z = 1.71 in normal tables gives a value of 0.4564 which is the probability that the value lies between 51 and 57, so the probability of it being less than 51 is 0.5 - 0.4564 = 0.0436 = 4.36 % The probability of getting less than 51 mpg is approx 4.36 %
The probability is 4/52 for the first ace and 3/51 for the second. So the probability of 2 aces is 4/52 x 3/51 = 1/221
For 51 10 19 32 23 47 67: σ=20.2308
The standard deviation = 23.856
15.72683482 is the standard deviation for that set of numbers.
8.919280881 is the standard deviation for those numbers.
For 51 11 21 394145: σ = 197,058.6674
One and 51 millionths (1.000051) in standard form is 1.000051 × 100
51/100 = 0.51 and in standard form 5.1*10-1
51%
Set 5 aside..51= 51/100-------------------so5 and 51/100-------------------------changed to improper fraction(100*5+51)/100= 551/100--------------------simplest form
n probability theory and statistics, thestandard deviation of a statistical population, a data set, or a probability distribution is the square root of itsvariance. Standard deviation is a widely used measure of the variability ordispersion, being algebraically more tractable though practically less robustthan the expected deviation or average absolute deviation.It shows how much variation there is from the "average" (mean). A low standard deviation indicates that the data points tend to be very close to the mean, whereas high standard deviation indicates that the data are spread out over a large range of values.For example, the average height for adult men in the United States is about 70 inches (178 cm), with a standard deviation of around 3 in (8 cm). This means that most men (about 68 percent, assuming a normal distribution) have a height within 3 in (8 cm) of the mean (67-73 in (170-185 cm)) - one standard deviation, whereas almost all men (about 95%) have a height within 6 in (15 cm) of the mean (64-76 in (163-193 cm)) - 2 standard deviations. If the standard deviation were zero, then all men would be exactly 70 in (178 cm) high. If the standard deviation were 20 in (51 cm), then men would have much more variable heights, with a typical range of about 50 to 90 in (127 to 229 cm). Three standard deviations account for 99.7% of the sample population being studied, assuming the distribution is normal (bell-shaped).
It is: (100+51)/2 = 75.5
1 and 51 millionths in standard form = 1.000051