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When you have a normal distribution and you know that the area above a given value of x is .35 you also know that?
Wiki User
∙ 6y ago
You also know that x is 1.036 times the standard deviation of the variable above its mean. Anything more than that would require further information about the mean and/or the variance of the variable.
Wiki User
∙ 6y ago
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In the Standard Normal Distribution 2.5 of the data lies above the standardized value of z?
No, they do not.
The total area under a normal distribution is infinite?
The total area under a normal distribution is not infinite. The total area under a normal distribution is a continuous value between any 2 given values. The function of a normal distribution is actually defined such that it must have a fixed value. For the "standard normal distribution" where μ=0 and σ=1, the area under the curve is equal to 1.
Is it true or false that The area under a normal distribution curve is always positive even if the z value is negative?
It is true. Because the normal distribution is above the horizontal axis for all values, the area under it is a positive quantity no matter the z value.
What is the expected value of the standard normal distribution equal to?
The expected value of the standard normal distribution is equal to the total amount of the value. It is usually equal to it when the value works out to be the same.
What is the mean of a normal distribution?
It is the expected value of the distribution. It also happens to be the mode and median.It is the expected value of the distribution. It also happens to be the mode and median.It is the expected value of the distribution. It also happens to be the mode and median.It is the expected value of the distribution. It also happens to be the mode and median.
In the Standard Normal Distribution 2.5 of the data lies above the standardized value of z?
No, they do not.
The total area under a normal distribution is infinite?
The total area under a normal distribution is not infinite. The total area under a normal distribution is a continuous value between any 2 given values. The function of a normal distribution is actually defined such that it must have a fixed value. For the "standard normal distribution" where μ=0 and σ=1, the area under the curve is equal to 1.
What is the different between standard normal distribution and normal distribution?
A normal distribution can have any value for its mean and any positive value for its variance. A standard normal distribution has mean 0 and variance 1.
Is it true or false that The area under a normal distribution curve is always positive even if the z value is negative?
It is true. Because the normal distribution is above the horizontal axis for all values, the area under it is a positive quantity no matter the z value.
What is the expected value of the standard normal distribution equal to?
The expected value of the standard normal distribution is equal to the total amount of the value. It is usually equal to it when the value works out to be the same.
Why is only one normal distribution table needed to find any probability under the normal curve?
The normal distribution is symmetric about its mean; it increases from an asymptote with the x-axis below the mean until the mean whereupon it decreases until another asymptote with the x-axis the same distance above the mean. (This is not a linear increase/decrease, but a "bell" shape.) As the distribution is symmetric about its mean, only tables up to the mean need be calculated/given in a table. The area under the curve between any two points can then be calculated. For a normal distribution with mean µ and standard deviation σ, a z value is calculated for a given point x: z = (x - µ) / σ This z value is then used to look up the area in the given "half" tables, giving the area (probability) of the value lying between the mean and the given z value. If negative, z is below the mean, but for the table, the sign is ignored. This can be expressed as: area = normal(|z|) where normal(z) is the value in the normal table at the given (positive) z value. To calculate the area between two points (ie the probability that a value lies between two given values), their corresponding z values (z₁ and z₂) are first calculated and then combined viz: If they are both on the same side of the mean (ie z₁ and z₂ have the same sign) then the area is given by:area = | normal(|z₁|) - normal(|z₂|) | If they are on opposite sides of the mean (ie z₁ and z₂ have different signs) then the area is given by:area = normal(|z₁|) + normal(|z₂|) Almost all of the normal distribution lies between ±4 standard deviations of the mean.
Is normal distribution bimodel?
No. Normal distribution is uni-modal, specifically with the mean, mode, and median at the same value.
What is the mean of a normal distribution?
It is the expected value of the distribution. It also happens to be the mode and median.It is the expected value of the distribution. It also happens to be the mode and median.It is the expected value of the distribution. It also happens to be the mode and median.It is the expected value of the distribution. It also happens to be the mode and median.
What is the meaning of random variable in probability distribution?
It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.It is a variable that can take a number of different values. The probability that it takes a value in any given range is determined by a random process and the value of that probability is given by the probability distribution function.
Another name for a standardized value of an observation in a normal distribution?
zscore
For a normal distribution what z-score value separates the lowest 10 percent of the scores from the rest of the distribution?
-1.28
If z value is greater than the values given in standard normal distribution curve table what value should be taken?
If the z value is that great the probability of the event is ridiculously small (or large) and you'd have to act as if it were near enough zero (or 1)
