The Normal Distribution

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# The Normal Distribution - PowerPoint PPT Presentation

The Normal Distribution. And the standard normal distribution (also known as the “bell curve”). The Mathematics of the Normal Distribution. The normal distribution is completely described by only two parameters: the mean μ and the standard deviation σ. Review: Binomial Distribution.

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### The Normal Distribution

And the standard normal distribution (also known as the “bell curve”)

The Mathematics of the Normal Distribution

The normal distribution is completely described by only two parameters: the mean μ and the standard deviation σ

Review: Binomial Distribution

The Binomial Distribution is the outcome of a Bernoulli trial (only two possible values) repeated n times, with probability p of success. In the notation, x is the number of successes.

Binomial Example

P = 0.25 (correct answer from a, b, c or d)

N = 10 questions

What is the probability of getting exactly 3 questions correct?

Binomial Dist. >>> Normal Dist.

The Normal Distribution is a continuous distribution, and is a limiting case of a (discrete) binomial distribution.

As the number of trials n -> ∞, the binomial distribution will approach the normal distribution.

Here n = 5; experiment simulated 1,000 times.

The binomial random variable X = number of success out of n = 5 trials, with probability p = 0.1 of success, repeated 1,000 times.

Simulation Continued (n increases)

P = 0.1, n = 10

Simulated 1,000 times.

P = 0.1, n = 25

Simulated 1,000 times.

Simulation Continued (n increases)

P = 0.1, n = 25

Simulated 1,000 times.

P = 0.1, n = 50

Simulated 1,000 times.

Other Simulations

P = 0.5, n = 10

Simulated 1,000 times.

P = 0.6, n = 100

Simulated 1,000 times.

Normal Distributions: Changing μ or σ

Same mean μ

Different standard deviation σ

Different mean μ

Same standard deviation σ

Normal Distributions: Changing both μ and σ

Different mean μand

Different standard deviation σ

The Sigma (standard deviation) Rule revisited

68% of the results will be between + or – 1 standard deviation (σ) away from the mean (μ).

95% of the results will be between + or – 2 standard deviation (σ) away from the mean (μ).

The Sigma (standard deviation) Rule revisited

99.7% of the results will be between + or – 3 standard deviation (σ) away from the mean (μ).

How to use a z-score

Standard normal (Z-score) tables can tell you the probability of getting between the z-score and the mean 0.

* Alternatively, the standard normal table could tell you the probability of getting a score anywhere below the z-score.

Sample Standard Normal Table

To economize on space, the standard normal table has the first digit of the z-score down the first column, and the second digit of the z-score across the first row.

Example: z = 0.92

0.3212

0.50

Pr(z ≤ 0.92) = 0.50 + 0.3212 = 0.8212

Standard Normal Curve: Example

* Note that if we looked at P (-2 ≤ z ≤ ++2) = 0.4772 x 2 ≈ 0.95 or 95%, which is the 2-sigma rule.

Standard Normal Curve: Example
• Note that the probability of getting a z-score less than z = -1.8 is P(z ≤ -1.8) = 1 – 0.50 – 0.4641 = 0.0359.
Applying the Standard Normal Distribution
• If the underlying distribution is approximately normal……
• … Transform the normal variable into a standard normal variable using its z-score.
• Solve the problem as above.