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What is the probability density function the mean and the variance Let the moments of a X be defined by EX equals 0.8?
Wiki User
∙ 14y ago
If E(x) = 0.8, then the mean of the distribution is 0.8. You have not provided enough information to completely answer this question.
Wiki User
∙ 14y ago
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Could f be a probability density function?
No. f is a letter of the Roman alphabet. It cannot be a probability density function.
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.
What is the difference between a probability density curve and cummulative distribution function?
what is density curve
Similarities between the variance and mean?
Beyond the fact that they are both measures derived from probability density functions, I cannot think of any similarity.
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.
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).
Is uniform distribution bimodal?
The modes of a probability density function might be defined as the (countable) set of points in the domain of the function for which the function achieves local maxima. Since the probability density function for the uniform distribution is constant by definition it has no local maxima, hence no modes. Hence, it cannot be bimodal.
Could f be a probability density function?
No. f is a letter of the Roman alphabet. It cannot be a probability density function.
Distinguish between binomial distribution and normal distribution?
Normal distribution is the continuous probability distribution defined by the probability density function. While the binomial distribution is discrete.
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.
How do you convert a beta probability density function to a beta frequency distribution?
probability density distribution
What does it mean for a population to be normally distributed?
A Gaussian distribution is the "official" term for the Normal distribution. This is a probability density function, of the exponential family, defined by the two parameters, its mean and variance. A population is said to be normally distributed if the values that a variable of interest can take have a normal or Gaussian distribution within that population.
What pdf stands for in statistics?
Probability Density Function
How do you find the probability density function?
The probability density function of a random variable can be either chosen from a group of widely used probability density functions (e.g.: normal, uniform, exponential), based on theoretical arguments, or estimated from the data (if you are observing data generated by a specific density function). More material on density functions can be found by following the links below.
What is the difference between a probability density curve and cummulative distribution function?
what is density curve
What best describes the distribution of the data?
A probability density function.
What is the difference between a probability mass function and a probability density function?
The probability mass function is used to characterize the distribution of discrete random variables, while the probability density function is used to characterize the distribution of absolutely continuous random variables. You might want to read more about this at www.statlect.com/prbdst1.htm (see the link below or on the right)
