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When studying the sum (or average) of a large number of independent variables.
A large number is necessary for the Central Limit Theorem to kick in - unless the variables themselves were normally distributed.
Independence is critical. If they are not, normality may not be assumed.
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For the normal distribution does it always require a continuity correction?
Use the continuity correction when using the normal distribution to approximate a binomial distribution to take into account the binomial is a discrete distribution and the normal distribution is continuous.
How does the standard normal distribution differ from the t-distribution?
The normal distribution and the t-distribution are both symmetric bell-shaped continuous probability distribution functions. The t-distribution has heavier tails: the probability of observations further from the mean is greater than for the normal distribution. There are other differences in terms of when it is appropriate to use them. Finally, the standard normal distribution is a special case of a normal distribution such that the mean is 0 and the standard deviation is 1.
When we use f distribution?
When comparing the sums of squares of normal variates.
Does a normal probability distribution include a bimodal distribution?
No, the normal distribution is strictly unimodal.
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.
For the normal distribution does it always require a continuity correction?
Use the continuity correction when using the normal distribution to approximate a binomial distribution to take into account the binomial is a discrete distribution and the normal distribution is continuous.
Why is it necessary to use a continuity correction when using a normal distribution to approximate a binomial distribution?
It is necessary to use a continuity correction when using a normal distribution to approximate a binomial distribution because the normal distribution contains real observations, while the binomial distribution contains integer observations.
Can normal distribution be used if the data is not normal?
You can use a normal distribution to approximate a binomial distribution if conditions are met such as n*p and n*q is > or = to 5 & n >30.
How does the standard normal distribution differ from the t-distribution?
The normal distribution and the t-distribution are both symmetric bell-shaped continuous probability distribution functions. The t-distribution has heavier tails: the probability of observations further from the mean is greater than for the normal distribution. There are other differences in terms of when it is appropriate to use them. Finally, the standard normal distribution is a special case of a normal distribution such that the mean is 0 and the standard deviation is 1.
Why the normal distribution can be used as an approximation to the binomial distribution?
The central limit theorem basically states that for any distribution, the distribution of the sample means approaches a normal distribution as the sample size gets larger and larger. This allows us to use the normal distribution as an approximation to binomial, as long as the number of trials times the probability of success is greater than or equal to 5 and if you use the normal distribution as an approximation, you apply the continuity correction factor.
What is the difference between a normal distribution and the standard normal distribution?
The standard normal distribution is a normal distribution with mean 0 and variance 1.
What is the difference of a normal distribution and a stardard normal distribution?
The standard normal distribution is a special case of the normal distribution. The standard normal has mean 0 and variance 1.
Pepsi has any competitive advantage with the use of normal distribution?
No.
Is continuous distribution normal distribution?
le standard normal distribution is a normal distribution who has mean 0 and variance 1
Which is the proper distribution to use when the interval estimation of m when s is assumed known?
standard normal distribution
When can you say the distribution is considered normal?
When its probability distribution the standard normal distribution.
When we use f distribution?
When comparing the sums of squares of normal variates.
