Question

10% items below 35 and 5° of above 90 then Find mean and verlonce of the normal distribution?
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Answer 1

Step-by-step explanation:

So far we have dealt with random variables with a finite

number of possible values. For example; if X is the number

of heads that will appear, when you flip a coin 5 times, X

can only take the values 0, 1, 2, 3, 4, or 5.

Some variables can take a continuous range of values, for

example a variable such as the height of 2 year old children

in the U.S. population or the lifetime of an electronic

component. For a continuous random variable X, the

analogue of a histogram is a continuous curve (the

probability density function) and it is our primary tool in

finding probabilities related to the variable. As with the

histogram for a random variable with a finite number of

values, the total area under the curve equals 1.Probabilities correspond to areas under the curve and are

calculated over intervals rather than for specific values of

the random variable.

Although many types of probability density functions

commonly occur, we will restrict our attention to random

variables with Normal Distributions and the probabilities

will correspond to areas under a Normal Curve (or

normal density function).

This is the most important example of a continuous

random variable, because of something called the Central

Limit Theorem: given any random variable with any

distribution, the average (over many observations) of that

variable will (essentially) have a normal distribution. This

makes it possible, for example, to draw reliable information

from opinion polls