0
Why is it that only one normal distribution table is needed to find any probability under the normal curve?
Anything that is normally distributed has certain properties. One is that the bulk of scores will be near the mean and the farther from the mean you are, the less common the score. Specifically, about 68% of anything that is normally distributed falls within one standard deviation of the mean.
That means that 68% of IQ scores fall between 85 and 115 (the mean being 100 and standard deviation being 15) AND 68% of adult male heights fall between 65 and 75 inches (the mean being 70 and I am estimating a standard deviation of 5).
Basically, even though the means and standard deviations change, something that is normally distributed will keep these probabilities (relative to the mean and standard deviation). By standardizing these numbers (changing the mean to 0 and the standard deviation to 1) we can use one table to find the probabilities for anything that is normally distributed.
Add your answer:
Earn +20 pts
Normal curve is the meaning of standard normal distribution?
No, the normal curve is not the meaning of the Normal distribution: it is one way of representing it.
Define a normal random variable?
I have included two links. A normal random variable is a random variable whose associated probability distribution is the normal probability distribution. By definition, a random variable has to have an associated distribution. The normal distribution (probability density function) is defined by a mathematical formula with a mean and standard deviation as parameters. The normal distribution is ofter called a bell-shaped curve, because of its symmetrical shape. It is not the only symmetrical distribution. The two links should provide more information beyond this simple definition.
What is the difference between a probability density curve and cummulative distribution function?
what is density curve
What is the math shape when it looks like a bow?
It could be a Gaussian curve (Normal distribution) rotated through a right angle.It could be a Gaussian curve (Normal distribution) rotated through a right angle.It could be a Gaussian curve (Normal distribution) rotated through a right angle.It could be a Gaussian curve (Normal distribution) rotated through a right angle.
How do you find the area of a normal distribution?
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.
Why if a probability distribution curve is bell shaped why is this a normal distribution?
A bell shaped probability distribution curve is NOT necessarily a normal distribution.
What does area have to do with probability?
A normalized probability distribution curve has an area under the curve of 1.Note: I said "normalized", not "normal". Do not confuse the terms.
What requirements are necessary for a normal probability distribution to be a standard normal probability distribution?
The normal distribution, also known as the Gaussian distribution, has a familiar "bell curve" shape and approximates many different naturally occurring distributions over real numbers.
If a probability distribution curve is bell-shaped then this is a normal distribution?
True * * * * * No. The Student's t-distribution, for example, is also bell shaped.
Is in the normal distribution the total area beneath the curve represent the probability for all possible outcomes for a given event?
Yes. The total area under any probability distribution curve is always the probability of all possible outcomes - which is 1.
What percentage of normally distributed scores lie under the normal curve?
100%. And that is true for any probability distribution.
Normal curve is the meaning of standard normal distribution?
No, the normal curve is not the meaning of the Normal distribution: it is one way of representing it.
How is probability related to the area under the normal curve?
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.
Define a normal random variable?
I have included two links. A normal random variable is a random variable whose associated probability distribution is the normal probability distribution. By definition, a random variable has to have an associated distribution. The normal distribution (probability density function) is defined by a mathematical formula with a mean and standard deviation as parameters. The normal distribution is ofter called a bell-shaped curve, because of its symmetrical shape. It is not the only symmetrical distribution. The two links should provide more information beyond this simple definition.
If the tails of the normal distribution curve are infinitely long. Is it True or False that the total area under the curve is also infinite?
False. A normalized distribution curve (do not confuse normalized with normal), by definition, has an area under the curve of exactly 1. That is because the probability of all possible events is also always exactly 1. The shape of the curve does not matter.
What is the area under a curve with mu equals 15 and sigma equals 2?
If the question is to do with a probability distribution curve, the answer is ONE - whatever the values of mu and sigma. The area under the curve of any probability distribution curve is 1.
What is the difference between a probability density curve and cummulative distribution function?
what is density curve
