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# Continuous Distributions

Model heights, stocks, or just about anything else with these distributions.

While an infinite number of distributions could be constructed to model a continuous random variable, there are only a handful that have found wide applicability to real-world data sets. These quizzes explore the most important continuous distributions, and how to determine which one is a good fit for a given situation:

- Normal
- Exponential
- Gamma
- Log-normal

The normal distribution provides an excellent approximation to a number of practical situations. It can be shown pictorially:

The main properties are that the normal distribution is **symmetric** about its mean, and decreasing in both directions from the center. Though this is true of other distributions as well, these signals are often enough to conclude the normal distribution is a good approximation.

A portfolio consists of 9 independent stocks, each of which have an average return of $0.15 and a standard deviation of $0.40. What is the average return and standard deviation of the overall portfolio?

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