Prob(X > 0.57) = Prob(Z > 2) = 0.02275 = 2.275%
84% To solve this problem, you must first realize that 66 inches is one standard deviation below the mean. The empirical rule states that 34% will be between the mean and 1 standard deviation below the mean. We are looking for the prob. of the height being greater than 66 inches, which is then 50% (for the entire right side of the distribution) + 34%
Step-By-Step: 5x30=150 It is not greater.
Greater than
327 inches is greater.
500 inches is 20 inches greater than 480 inches (40 feet)
3
Standard deviation = square root of variance.
2.3
84% To solve this problem, you must first realize that 66 inches is one standard deviation below the mean. The empirical rule states that 34% will be between the mean and 1 standard deviation below the mean. We are looking for the prob. of the height being greater than 66 inches, which is then 50% (for the entire right side of the distribution) + 34%
A standard deviation is a statistical measure of the variation there in a population or group. A standard deviation of 1 means that 68% of the members of the population are withing plus or minus the value of the standard deviation from the average. For example: assume the average height of men is 5 feet 9 inches, and the standard deviation is three inches. Then 68% of all men are between 5' 6" and 6' which is 5'9" plus or minus 3 inches. [Note: this is only to illustrate and is not intended to be a real/correct statistic of men's heights.]
A normal distribution with a mean of 65 and a standard deviation of 2.5 would have 95% of the population being between 60 and 70, i.e. +/- two standard deviations.
45.665 inches Type your answer here... what is the answer??
Suppose a normal random variable has a mean of 72 inches and a standard deviation of 2 inches. Suppose the random variable X measures the height of adult males in a certain city. One may therefore conclude that approximately 84% of the men in this population are shorter than?
Mean = 163.4/2.54 = 64.33 inches approx, and sd = 6.7/2.54 = 2.64 inches, approx.
Anything that is normally distributed has certain properties. One is that the bulk of scores will be near the mean and the farther from the mean you are, the less common the score. Specifically, about 68% of anything that is normally distributed falls within one standard deviation of the mean. That means that 68% of IQ scores fall between 85 and 115 (the mean being 100 and standard deviation being 15) AND 68% of adult male heights fall between 65 and 75 inches (the mean being 70 and I am estimating a standard deviation of 5). Basically, even though the means and standard deviations change, something that is normally distributed will keep these probabilities (relative to the mean and standard deviation). By standardizing these numbers (changing the mean to 0 and the standard deviation to 1) we can use one table to find the probabilities for anything that is normally distributed.
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).
Yes, 0.5 inches is greater than 0.093 inches.