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What condition must be met to use the normal distribution to approximate the binomial distribution?
A large sample (n > 25) and p, the probability of success on each trial = around 0.5 (0.35 to 0.65).
Independence is already assumed for it to be binomial.
A large sample (n > 25) and p, the probability of success on each trial = around 0.5 (0.35 to 0.65).
Independence is already assumed for it to be binomial.
A large sample (n > 25) and p, the probability of success on each trial = around 0.5 (0.35 to 0.65).
Independence is already assumed for it to be binomial.
A large sample (n > 25) and p, the probability of success on each trial = around 0.5 (0.35 to 0.65).
Independence is already assumed for it to be binomial.
What else can I help you with?
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.
Can you use the normal distribution to approximate the binomial distribution. Give reason?
Yes, and the justification comes from the Central Limit Theorem.
Are all symmetric distribution are normal?
No. The binomial distribution (discrete) or uniform distribution (discrete or continuous) are symmetrical but they are not normal. There are others.
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.
Is the normal distribution infinite?
The domain of the normal distribution is infinite.
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.
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.
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.
Can you use the normal distribution to approximate the binomial distribution. Give reason?
Yes, and the justification comes from the Central Limit Theorem.
What is normal binomial distribution?
There is no such thing. The Normal (or Gaussian) and Binomial are two distributions.
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.
Derive normal distribution as a limiting case of binomial distribution?
ref veeru
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.
When can a binomial situation be approxiamted with a normal distribution?
The binomial distribution can be approximated with a normal distribution when np > 5 and np(1-p) > 5 where p is the proportion (probability) of success of an event and n is the total number of independent trials.
Are all symmetric distribution are normal?
No. The binomial distribution (discrete) or uniform distribution (discrete or continuous) are symmetrical but they are not normal. There are others.
Can normal distribution be applied on discrete data?
Yes. The normal distribution is used to approximate a binomial distribution when the sample size (n) times the probability of success (p), and the probability of failure (q) are both greater than or equal to 5. The mean of the normal approximation is n*p and the standard deviation is the square root of n*p*q.
List of common symmetric distributions?
A small partial list includes: -normal (or Gaussian) distribution -binomial distribution -Cauchy distribution
