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le standard normal distribution is a normal distribution who has mean 0 and variance 1

Q: Is continuous distribution normal distribution

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The normal distribution is always continuous.

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.

The statement is false. The binomial distribution (discrete) or uniform distribution (discrete or continuous) are symmetrical but they are not normal. There are others.

The total area under a normal distribution is not infinite. The total area under a normal distribution is a continuous value between any 2 given values. The function of a normal distribution is actually defined such that it must have a fixed value. For the "standard normal distribution" where μ=0 and σ=1, the area under the curve is equal to 1.

If the question is asking if a continuous distribution can be converted to a discrete distribution, the answer is yes. Your age has a continuous distribution but in most cases, the information is recorded and analysed as if it were the whole number of years - a discrete distribution.

Related questions

The normal distribution is always continuous.

Yes, the normal distribution, standard or not is always continuous.

No. Normal distribution is a continuous probability.

No, it's a continuous distribution.

we prefer normal distribution over other distribution in statistics because most of the data around us is continuous. So, for continuous data normal distribution is used.

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.

Infinitely many. The normal distribution is applicable to a continuous variable whose domain is the whole of the real numbers. Infinitely many. The normal distribution is applicable to a continuous variable whose domain is the whole of the real numbers. Infinitely many. The normal distribution is applicable to a continuous variable whose domain is the whole of the real numbers. Infinitely many. The normal distribution is applicable to a continuous variable whose domain is the whole of the real numbers.

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.

Normal distribution is the continuous probability distribution defined by the probability density function. While the binomial distribution is discrete.

The statement is false. The binomial distribution (discrete) or uniform distribution (discrete or continuous) are symmetrical but they are not normal. There are others.

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.

No. The binomial distribution (discrete) or uniform distribution (discrete or continuous) are symmetrical but they are not normal. There are others.