Question

Standard normal probability distribution has mean equal to 40, whereas value of random variable x is 80 and z-statistic is equal to 2 then standard deviation of standard normal probability distribution is

Answer 1

The normal distribution refers to a family of continuous probability distributions described by the normal equation.The Normal Equation

The normal distribution is defined by the following equation:

The Normal Equation. The value of the random variable Y is:

Y = { 1/[ σ * sqrt(2π) ] } * e-(x - μ)2/2σ2

where X is a normal random variable, μ is the mean, σ is the standard deviation, π is approximately 3.14159, and e is approximately 2.71828.

The random variable X in the normal equation is called the normal random variable. The normal equation is the probability density function for the normal distribution.

The Normal Curve

The graph of the normal distribution depends on two factors - the mean and the standard deviation. The mean of the distribution determines the location of the center of the graph, and the standard deviation determines the height and width of the graph. All normal distributions look like a symmetric, bell-shaped curve, as shown below.

Smaller standard deviation

Bigger standard deviation

When the standard deviation is small, the curve is tall and narrow; and when the standard deviation is big, the curve is short and wide (see above)

Probability and the Normal Curve

The normal distribution is a continuous probability distribution. This has several implications for probability.

The total area under the normal curve is equal to 1.

The probability that a normal random variable X equals any particular value is 0.

The probability that X is greater than a equals the area under the normal curve bounded by a and plus infinity (as indicated by the non-shaded area in the figure below).

The probability that X is less than a equals the area under the normal curve bounded by a and minus infinity (as indicated by the shaded area in the figure below).

Additionally, every normal curve (regardless of its mean or standarddeviation) conforms to the following "rule".

About 68% of the area under the curve falls within 1 standard deviation of the mean.

About 95% of the area under the curve falls within 2 standard deviations of the mean.

About 99.7% of the area under the curve falls within 3 standard deviations of the mean.

Collectively, these points are known as the empirical rule or the 68-95-99.7 rule. Clearly, given a normal distribution, most outcomes will be within 3 standard deviations of the mean.

To find the probability associated with a normal random variable, use a graphing calculator, an online normal distribution calculator, or a normal distribution table. In the examples below, we illustrate the use of Stat Trek's Normal Distribution Calculator, a free tool available on this site. In the next lesson, we demonstrate the use of normal distribution tables.

Normal Distribution Calculator

The normal distribution calculator solves common statistical problems, based on the normal distribution. The calculator computes cumulative probabilities, based on three simple inputs. Simple instructions guide you to an accurate solution, quickly and easily. If anything is unclear, frequently-asked questions and sample problems provide straightforward explanations. The calculator is free. It can found in the Stat Trek main menu under the Stat Tools tab. Or you can tap the button below.

Normal Distribution Calculator

Test Your Understanding

Problem 1

An average light bulb manufactured by the Acme Corporation lasts 300 days with a standard deviation of 50 days. Assuming that bulb life is normally distributed, what is the probability that an Acme light bulb will last at most 365 days?

Solution: Given a mean score of 300 days and a standard deviation of 50 days, we want to find the cumulative probability that bulb life is less than or equal to 365 days. Thus, we know the following:

The value of the normal random variable is 365 days.

The mean is equal to 300 days.

The standard deviation is equal to 50 days.

We enter these values into the Normal Distribution Calculator and compute the cumulative probability. The answer is: P( X < 365) = 0.90. Hence, there is a 90% chance that a light bulb will burn out within 365 days.

Answer 2

The standard deviation of standard normal probability distribution is 20.

Explanation:

Formula for z-score :

$z=\dfrac{x-\mu}{\sigma}$ , where x= random variable ,  $\mu$ = mean and $\sigma$ = standard deviation  of standard normal probability distribution.

As per given , we have

x= 80

$\mu=40$

z=2

To find  $\sigma$.

Substitute all values in formula , we get

$2=\dfrac{80-40}{\sigma}\\\\ 2=\dfrac{40}{\sigma}\\\\ \sigma = \dfrac{40}{2}=20$

Hence, the standard deviation of standard normal probability distribution is 20.

# Learn more :

If value of x for normal distribution is 35, mean of normal distribution is 65 and standard deviation is 25 then standardized random variable is

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