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What is the probability that a gaussian probability density function will take a value less than -2?
Wiki User
∙ 14y ago
Assuming that you are considering a N(0,1) Gaussian distribution, the answer is approximately 1 in 20. The 0.95%ile (two tailed) occurs at -1.96 and 1.96.
Wiki User
∙ 14y ago
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Why will a density curve always give a probability of zero?
It will not. For the interval (x, x+dx) it may well give a non-zero probability. With a continuous distribution, the probability of any particular value is always 0. What the probability density function gives is the probability that the variable is NEAR the selected value.
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.
How is probability related to the area under the normal curve?
The Normal curve is a graph of the probability density function of the standard normal distribution and, as is the case with any continuous random variable (RV), the probability that the RV takes a value in a given range is given by the integral of the function between the two limits. In other words, it is the area under the curve between those two values.
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.
How do you get the median of a continuous random variable?
You integrate the probability distribution function to get the cumulative distribution function (cdf). Then find the value of the random variable for which cdf = 0.5.
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.
The mode is the largest value in a symmetric distribution?
Yes- the highest probability value is the mode. Let me clarify this answer: For a probability mass function for a discrete variables, the mode is the value with the highest probability as shown on the y axis. For a probability density function for continuous variables, the mode is the value with the highest probability density as shown on the y-axis.
Does the probability that a continuous random variable take a specific value depend on the probability density function?
No. The probability that a continuous random variable takes a specific value is always zero.
Why will a density curve always give a probability of zero?
It will not. For the interval (x, x+dx) it may well give a non-zero probability. With a continuous distribution, the probability of any particular value is always 0. What the probability density function gives is the probability that the variable is NEAR the selected value.
What name is given to a statistical graph where a quantity is represented by a curve and has the same value everywhere along the?
A uniform probability density function.
For a continuous random variable the probability that the value of x is greater than a given constant is?
The integral of the density function from the given point upwards.
Steps for how to do a z-score problem in statistics?
If you have a variable X distributed with mean m and standard deviation s, then the z-score is (x - m)/s. If X is normally distributed, or is the mean of a random sample then Z has a Standard Normal distribution: that is, a Gaussian distribution with mean 0 and variance 1. The probability density function of Z is tabulated so that you can check the probability of observing a value as much or more extreme.
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.
How do you use 3.14?
It is an approximate value for pi. In elementary mathematics, pi is the ratio of the circumference of a circle to its diameter. In more advanced mathematics, it crops up in the most unexpected laces - for example, in the probability density functions for the Normal (Gaussian) distribution, Student's t distribution - of the t-test.
What is the Probability density function of Poisson distribution?
If a random variable X has a Poisson distribution with parameter l, then the probability that X takes the value x isPr(X = x) = lx*e-l/x! for x = 0, 1, 2, 3, ...
What are some examples where the mean the median and the mode might be the same?
(10, 15, 15, 15, 20) The answer above displays a sample in which the sample mean, sample median and sample mode assume the same value. If you were asking about populations, then the population mean, population median and population mode are the same whenever the probability density function for the population is symmetric. For example, the normal probability density function is symmetric, the t and uniform density functions are symmetric. Many are.
How is probability related to the area under the normal curve?
The Normal curve is a graph of the probability density function of the standard normal distribution and, as is the case with any continuous random variable (RV), the probability that the RV takes a value in a given range is given by the integral of the function between the two limits. In other words, it is the area under the curve between those two values.
