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Suppose z has a standard normal distribution with a mean of 0 and a standard deviation of 1. the probability that z is less than 1.15 is?
Wiki User
∙ 11y ago
probability is 43.3%
Wiki User
∙ 11y ago
charles davis Sevill...
0.3636
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Suppose the standard deviation is 13.1 what is the variance?
13.1 squared = 3.62
Suppose the variance is 64 Find the standard deviation?
Standard deviation is the square root of the variance; so if the variance is 64, the std dev is 8.
Mean and standard deviation of probability density function?
Suppose the probability density function is f(x), defined over a domain D Then the mean is E(X) = x*f(x) integrated with respect to x over D. Calculate E(X2) = x2*f(x) integrated with respect to x over D. Then Variance(X) = E(X2) - [E(X)]2 and Standard Deviation = sqrt(Variance).
The distribution of the amount of change in UF student's pockets has an average of 2.02 dollars and a standard deviation of 3.00 dollars Suppose that a random sample of 45 UF students was taken and ea?
It would be approximately normal with a mean of 2.02 dollars and a standard error of 3.00 dollars.
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 con?
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?
Suppose a normal distribution has a mean of 50 and a standard deviation of 3. What is P(x≤53)?
0.84
Suppose the standard deviation is 12.4 What is the variance?
12.4
Suppose that a population that a population has mean equals 64 and standard deviation equals 18. A sample of size 36 is selected. What is the mean of the sampling distribution of means?
64.
Suppose the standard deviation is 13.1 what is the variance?
13.1 squared = 3.62
Suppose the variance is 64 Find the standard deviation?
Standard deviation is the square root of the variance; so if the variance is 64, the std dev is 8.
Suppose the standard deviation is 36 Find the variance?
Variance is 362 or 1296.
Mean and standard deviation of probability density function?
Suppose the probability density function is f(x), defined over a domain D Then the mean is E(X) = x*f(x) integrated with respect to x over D. Calculate E(X2) = x2*f(x) integrated with respect to x over D. Then Variance(X) = E(X2) - [E(X)]2 and Standard Deviation = sqrt(Variance).
The distribution of the amount of change in UF student's pockets has an average of 2.02 dollars and a standard deviation of 3.00 dollars Suppose that a random sample of 45 UF students was taken and ea?
It would be approximately normal with a mean of 2.02 dollars and a standard error of 3.00 dollars.
What is the relevance of calculating standard deviation?
The Standard Deviation will give you an idea of how 'spread apart' the data is. Suppose the average gasoline prices in your town are 2.75 per gallon. A low standard deviation means many of the gas stations will have prices close to that price, while a high standard deviation means you would find prices much higher and also much lower than that average price.
What do you mean when you say that the coefficient of variation has no units?
Suppose the mean of a sample is 1.72 metres, and the standard deviation of the sample is 3.44 metres. (Notice that the sample mean and the standard deviation will always have the same units.) Then the coefficient of variation will be 1.72 metres / 3.44 metres = 0.5. The units in the mean and standard deviation 'cancel out'-always.
What is marginal probability?
Suppose you have two random variables, X and Y and their joint probability distribution function is f(x, y) over some appropriate domain. Then the marginal probability distribution of X, is the integral or sum of f(x, y) calculated over all possible values of Y.
What determines the standard deviation to be high?
Standard deviation is a measure of the scatter or dispersion of the data. Two sets of data can have the same mean, but different standard deviations. The dataset with the higher standard deviation will generally have values that are more scattered. We generally look at the standard deviation in relation to the mean. If the standard deviation is much smaller than the mean, we may consider that the data has low dipersion. If the standard deviation is much higher than the mean, it may indicate the dataset has high dispersion A second cause is an outlier, a value that is very different from the data. Sometimes it is a mistake. I will give you an example. Suppose I am measuring people's height, and I record all data in meters, except on height which I record in millimeters- 1000 times higher. This may cause an erroneous mean and standard deviation to be calculated.
