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The Normal ApproximationPowerPoint Presentation

The Normal Approximation

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The Normal Approximation

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The Normal Approximation

Unit 5, Day 4

- I can identify the relationship between the Binomial Distribution and the Normal Distribution.
- I can state and find the mean and standard deviations used to approximate binomial distributions.
- I can solve problems using Normal Approximation using various aids(examples, notes, etc.).

We have seen that probabilities can be calculated using the formula for a binomial distribution provided that:

- Each trial in the experiment is identical.
- The outcomes of each trial can be classified as success or failure

A regular die is rolled 100 times and the number of 5’s that appear is recorded. Determine the probability that at most twenty 5’s are rolled.

Above are two graphs that show the probability distributions for the number of 5’s rolled based on 5 and 50 trials. What do you notice?

Key Point: As the number of trials increase, the Binomial Distribution can be modeled using the Normal Distribution!!!!!

If X has a binomial distribution with n trials and probability of success p, then it can be approximated by a normal distribution with

and

provided that np>= 5 and nq>=5

This means that we can take those huge binomial distribution questions, convert over to a Normal Distribution, and use z-scores to solve it!

One issue is the fact that a Binomial Distribution is discrete (contains only countable outcomes) and a Normal Distribution is continuous.

To account for this, we use a continuity correction (a value of +/- 0.5):

For example:

is corrected to

is corrected to

A regular die is rolled 100 times and the number of 5’s that appear is recorded. Determine the probability that at most twenty 5’s are rolled.

A coin is tossed 60 times.

- Find the probability that you toss tails exactly 25 times.
- Estimate the probability you get tails 25 or more times.

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