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What are the Similarities of discrete probability distribution and continuous probability distribution?
They are probability distributions!
The binomial and Poisson distributions are examples of discrete probability distributions?
discrete & continuous
Is the total area within any continuous probability distribution is equal to 1.00?
Yes, but not just continuous prob distribs. It applies to discontinous or discrete distributions as well.
Does this means that all symmetric distribution are normal Explain?
Don't know what "this" is, but all symmetric distributions are not normal. There are many distributions, discrete and continuous that are not normal. The uniform or binomial distributions are examples of discrete symmetric distibutions that are not normal. The uniform and the beta distribution with equal parameters are examples of a continuous distribution that is not normal. The uniform distribution can be discrete or continuous.
What are the 4 probabilities?
There are not just 4 probabilities. Probability is a continuous variable ranging from 0 to 1: it can take infinitely many values.There are not just 4 probabilities. Probability is a continuous variable ranging from 0 to 1: it can take infinitely many values.There are not just 4 probabilities. Probability is a continuous variable ranging from 0 to 1: it can take infinitely many values.There are not just 4 probabilities. Probability is a continuous variable ranging from 0 to 1: it can take infinitely many values.
What are the Similarities of discrete probability distribution and continuous probability distribution?
They are probability distributions!
The binomial and Poisson distributions are examples of discrete probability distributions?
discrete & continuous
Similarity between the uniform and normal probability distributions?
They are continuous, symmetric.
What is probability mass function?
It is a function which is usually used with continuous distributions, to give the probability associated with different values of the variable.
What kind of distribution is exponential distribution?
Exponential distribution is a function of probability theory and statistics. This kind of distribution deals with continuous probability distributions and is part of the continuous analogue of the geometric distribution in math.
What type of probability distribution is the normal distribution?
It is a continuous parametric distribution belonging to the family of exponential distributions. It is also symmetric.
Is the total area within any continuous probability distribution is equal to 1.00?
Yes, but not just continuous prob distribs. It applies to discontinous or discrete distributions as well.
Do normal probability distributions have different arithmetic means and different standard deviations?
Yes. And that is true of most probability distributions.
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 Poisson probability distributions be simulated?
Yes.
What are the requirements for a probability distribution (Select all that apply.)?
A probability distribution must satisfy the following requirements: (1) The probabilities of all possible outcomes must sum to 1; (2) Each individual probability must be between 0 and 1, inclusive. Additionally, for discrete distributions, all probabilities must be non-negative, while for continuous distributions, the probability density function must be non-negative over its entire range.
Is binomial and poisson distributions descrete or continuous?
Both the binomial and Poisson distributions are discrete probability distributions. The binomial distribution models the number of successes in a fixed number of independent trials, while the Poisson distribution models the number of events occurring in a fixed interval of time or space. Since both deal with countable outcomes, they are classified as discrete distributions.
