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For some positive value of Z the probability that a standard normal variable is between 0 and z is 0.3770. The value of Z is?
Wiki User
∙ 12y ago
P(0 < Z < z) = 0.3770 is the same as looking at P(Z < z) = 0.8770 because the other half of the curve (anything less than 0) has probability of 0.5. Now this is a problem of just looking it up from the table. The table gives a value z = 1.16 for the probability of 0.8770. So P(0 < Z < 1.16) = 0.3770.
Wiki User
∙ 12y ago
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For some positive value of Z the probability that a standard normal variable is between 0 and Z is 0.3340. the value of Z is?
0.97
What is the probability that a standard normal variable will be between the values of -2 and 1?
0.636 approx.
True or False the probability that a standard normal random variable Z is between 1.50 and 2.10 is the same as the probability Z is between -2.10 and -1.50.?
It is true because the distribution is symmetrical about Z=0.
Difference between a random variable and a probability distribution is?
A random variable is a variable that can take different values according to a process, at least part of which is random.For a discrete random variable (RV), a probability distribution is a function that assigns, to each value of the RV, the probability that the RV takes that value.The probability of a continuous RV taking any specificvalue is always 0 and the distribution is a density function such that the probability of the RV taking a value between x and y is the area under the distribution function between x and y.
Is probability always positive?
The value of a probability is a number between 0 and 1 So it's either positive and less or equal to one or null
For some positive value of Z the probability that a standard normal variable is between 0 and Z is 0.3340. the value of Z is?
0.97
For some positive value of x the probability that a standard normal variable is between 0 and plus 1.5x is 0.4332 what is the value of x?
1
What is the probability that a standard normal variable will be between the values of -2 and 1?
0.636 approx.
True or False the probability that a standard normal random variable Z is between 1.50 and 2.10 is the same as the probability Z is between -2.10 and -1.50.?
It is true because the distribution is symmetrical about Z=0.
It's true or false that probability of standard normal random variable z is between 1.5 to 2.1 and is the same as the probability z is between -2.1 to -1.5?
True. Due to the symmetry of the normal distribution.
What is the probability the random variable will assume a value between 40 and 60?
It depends on what the random variable is, what its domain is, what its probability distribution function is. The probability that a randomly selected random variable has a value between 40 and 60 is probably quite close to zero.
What happens to the probability of observing a t-random variable between -2 and 2 as you increase the degrees of freedom?
The probability increases.The probability increases.The probability increases.The probability increases.
Difference between a random variable and a probability distribution is?
A random variable is a variable that can take different values according to a process, at least part of which is random.For a discrete random variable (RV), a probability distribution is a function that assigns, to each value of the RV, the probability that the RV takes that value.The probability of a continuous RV taking any specificvalue is always 0 and the distribution is a density function such that the probability of the RV taking a value between x and y is the area under the distribution function between x and y.
What is the formula for a random variable?
The formula, if any, depends on the probability distribution function for the variable. In the case of a discrete variable, X, this defines the probability that X = x. For a continuous variable, the probability density function is a continuous function, f(x), such that Pr(a < X < b) is the area under the function f, between a and b (or the definite integral or f, with respect to x, between a and b.
What does the probability density function tell you?
The area under the pdf between two values is the probability that the random variable lies between those two values.
What is the difference between probability distribution and probability density function?
A probability density function assigns a probability value for each point in the domain of the random variable. The probability distribution assigns the same probability to subsets of that domain.
Is probability always positive?
The value of a probability is a number between 0 and 1 So it's either positive and less or equal to one or null
