Let us learn about bell curve distribution
A continuous random variable X is denoted to follow a bell curve distribution with parameter μ and σ (or μ and σ2) if the probability functions is defined by
f(x) = 12Πσ e-12(x-μσ)2 ; - <> 0
X ~N(μ, σ) denotes that the random variable X follows bell curve distribution Even we can write the bell curve distribution as X~N(μ, σ2) symbolically. In this case the parameters are mean and standard deviation with mean μ and standard deviation σ. The bell curve distribution is also known as Gaussian distribution and also called as normal distribution.
bell curve distribution, which figure most significantly in statistical theory and in application. Normal distribution is also called as the Normal probability distribution. check out on how to calculate binomial probability distribution. The normal distribution looks like a bell shaped curve. Hence it is also known as normal bell curve distribution.
Get more detailed information on types of probability distribution
A continuous random variable X is denoted to follow a bell curve distribution with parameter μ and σ (or μ and σ2) if the probability functions is defined by
f(x) = 12Πσ e-12(x-μσ)2 ; - <> 0
X ~N(μ, σ) denotes that the random variable X follows bell curve distribution Even we can write the bell curve distribution as X~N(μ, σ2) symbolically. In this case the parameters are mean and standard deviation with mean μ and standard deviation σ. The bell curve distribution is also known as Gaussian distribution and also called as normal distribution.
bell curve distribution, which figure most significantly in statistical theory and in application. Normal distribution is also called as the Normal probability distribution. check out on how to calculate binomial probability distribution. The normal distribution looks like a bell shaped curve. Hence it is also known as normal bell curve distribution.
Get more detailed information on types of probability distribution
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