What Is a Normal Distribution in Statistics?

The normal distribution is the most important probability distribution.

Theory

Normal Distribution

The normal distribution with expectation value μ and standard deviation σ is described by the function

f(x) = 1 σ2πe(xμ)2 2σ2

Luckily, you will not be working with this function directly.

The probability of getting a result between a and b is given by the area bounded by the graph, the x-axis and vertical lines at x = a and x = b. P (a x b) can be found in a probability table or through the use of digital tools.

When you’re working with a normal distribution by hand, you need to convert the normal distribution into the standard normal distribution. Then, you can use the standardized table that contains all the solutions. A standardized normal distribution is a normal distribution with an expected value equal to 0 and a standard deviation equal to 1. When converting into the standard normal distribution, you use the following conversion formula:

Formula

Conversion to Standard Normal Distribution

Z = X μ σ

where the random variable Z is distributed just like the standard normal distribution.

Example 1

The birth weight of a newborn girl is considered normally distributed with an expectation value of 3.50kg and a standard deviation of 0.48kg.

1.
What is the probability that a random girl weighs less than 2.5kg when born?
2.
What is the probability that a random girl weighs more than 4.0kg when born?
3.
What is the probability that a random girl weighs between 2.5kg and 4.0kg when born?

1.
You want to find P (X 2.5). The calculation looks like this: P (X 2.5) = P (X μ σ 2.5 3.5 0.48 ) = P (Z 2.0833)

You look up the Z-value in the probability table for the normal distribution and find that

P (Z 2.0833) Z = 0.0188 = 1.88%

P (Z 2.0833) Z = 0.0188 = 1.88%

The probability of a new born girl weighing less than 2.5 kg is 1.88 %.

2.
You want to find P (X 4.0). The calculation looks like this: P (X 4.0) = 1 P (X 4.0) = 1 P (X μ σ 4.0 3.5 0.48 ) = 1 P (Z 1.04)

You look up the Z-value in the table and find that

P (Z 1.04) = 0.8508

which gives you that

1 P (Z 1.04) = 1 0.8508 = 0.1492 = 14.92%

The probability that a random newborn girl weighs more than 4.0 kg is 14.92 %.

3.
You want to find P (2.5 X 4.0). In this case, you have to set up a double inequality. It looks like this:
P (2.5 X 4.0) = P(2.5 3.5 0.48 X μ σ 4.0 3.5 0.48 ) = P(2.08 Z 1.04) = P (Z 1.04) P (Z 2.08)

P (2.5 X 4.0) = P (2.5 3.5 0.48 X μ σ 4.0 3.5 0.48 ) = P (2.08 Z 1.04) = P (Z 1.04) P (Z 2.08)

From the table you find the values of the respective Z-values, and their difference is

P (2.5 X 4.0) = 0.8508 0.0188 = 0.8320 = 83.2%

The probability that a random newborn girl weighs between 2.5 kg and 4.0 kg is 83.2 %.

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