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Q: An area of a normal probability distribution represents?

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The total area of any probability distribution is 1

Yes. The total area under any probability distribution curve is always the probability of all possible outcomes - which is 1.

The Normal curve is a graph of the probability density function of the standard normal distribution and, as is the case with any continuous random variable (RV), the probability that the RV takes a value in a given range is given by the integral of the function between the two limits. In other words, it is the area under the curve between those two values.

1. It is a probability distribution function and so the area under the curve must be 1.

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.

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The total area of any probability distribution is 1

50%

A normalized probability distribution curve has an area under the curve of 1.Note: I said "normalized", not "normal". Do not confuse the terms.

Yes. The total area under any probability distribution curve is always the probability of all possible outcomes - which is 1.

A researcher wants to go from a normal distribution to a standard normal distribution because the latter allows him/her to make the correspondence between the area and the probability. Though events in the real world rarely follow a standard normal distribution, z-scores are convenient calculations of area that can be used with any/all normal distributions. Meaning: once a researcher has translated raw data into a standard normal distribution (z-score), he/she can then find its associated probability.

The area under a normal distribution is one since, by definition, the sum of any series of probabilities is one and, therefore, the integral (or area under the curve) of any probability distribution from negative infinity to infinity is one. However, if you take an interval of a normal distribution, its area can be anywhere between 0 and 1.

-1.43 (approx)

z = 1.52 (approx)

Yes, it is true; and the 2 quantities that describe a normal distribution are mean and standard deviation.

1.

The Normal curve is a graph of the probability density function of the standard normal distribution and, as is the case with any continuous random variable (RV), the probability that the RV takes a value in a given range is given by the integral of the function between the two limits. In other words, it is the area under the curve between those two values.

1. It is a probability distribution function and so the area under the curve must be 1.

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