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Does empirical rules always apply to discrete probability distribution?
the empirical rules of probablility applies to the continuous probability distribution
What is the area under a discrete probability distribution function?
1.
Is normal distribution also a probability distribution?
Yes. When we refer to the normal distribution, we are referring to a probability distribution. When we specify the equation of a continuous distribution, such as the normal distribution, we refer to the equation as a probability density function.
Is a normal distribution discrete?
No, it's a continuous distribution.
What is a Bernoulli distribution?
A Bernoulli distribution is a discrete probability distribution which takes value 1 with success probability p and value 0 with failure probability q = 1 - p.
What discrete probability distribution can be approximated by a normal dsitribution?
If X has any discrete probability distribution then the sum of a number of observations for X will be normal.
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.
Is the binominal probability discrete or continuous?
The binomial probability distribution is discrete.
Is the Poisson probability distribution discrete or continuous?
The Poisson distribution is discrete.
What are the Similarities of discrete probability distribution and continuous probability distribution?
They are probability distributions!
When a continuous probability distribution is used to approximate a discrete probability distribution what value is added or subtracted?
Half the discrete unit.
What is The mean of a discrete probability distribution is also called the?
The mean of a discrete probability distribution is also called the Expected Value.
What are some examples of distribution function?
I will assume that you are asking about probability distribution functions. There are two types: discrete and continuous. Some might argue that a third type exists, which is a mix of discrete and continuous distributions. When representing discrete random variables, the probability distribution is probability mass function or "pmf." For continuous distributions, the theoretical distribution is the probability density function or "pdf." Some textbooks will call pmf's as discrete probability distributions. Common pmf's are binomial, multinomial, uniform discrete and Poisson. Common pdf's are the uniform, normal, log-normal, and exponential. Two common pdf's used in sample size, hypothesis testing and confidence intervals are the "t distribution" and the chi-square. Finally, the F distribution is used in more advanced hypothesis testing and regression.
Can normal distridution apply on discrete data?
Yes, If you have a large data set, you can approximate the discrete data by Normal distribution (which is continuous). An example would be, "A coin is tossed 1000 times. What is the probability of rolling between 300 and 400 heads?" This problem, usually solved by Binomial distribution (which is a discrete distribution), is very difficult to solve because of the large data set and can be approximated by the Normal distribution.
How does a discrete probability distribution differ from a continuous probability distribution?
A discrete probability distribution is defined over a set value (such as a value of 1 or 2 or 3, etc). A continuous probability distribution is defined over an infinite number of points (such as all values between 1 and 3, inclusive).
How the symmetric distribution is always normal?
The statement is false. The binomial distribution (discrete) or uniform distribution (discrete or continuous) are symmetrical but they are not normal. There are others.
Does empirical rules always apply to discrete probability distribution?
the empirical rules of probablility applies to the continuous probability distribution
