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IFT Notes for Level I CFA® Program

R09 Common Probability Distributions

Part 2


 

3. Continuous Random Variables

3.1.     Continuous Uniform Distribution

The continuous uniform distribution is defined over a range from a lower limit ‘a’ to an upper limit ‘b’. These limits serve as the parameters of the distribution.

 

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The probability that the random variable will take a value between x1 and x2, where x1 and x2 both lie within the range is given by:

P(x1 ≤ X ≤ x2) = \frac{x_2\ - \ x_1}{b \ - \ a}

 

Example

X is a uniformly distributed continuous random variable between 10 and 20. Calculate the probability that X will fall between 12 and 18.

Solution:

P(12 ≤ X ≤ 18) = \frac{ 18\ - \ 12}{ 20 \ - \ 10} = 0.6

 

The cumulative distribution function for a continuous random variable is shown below:

 

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Example

A commodity analyst predicts that the price per ounce of gold three years from now will be between $1,500 and $1,700. Assume gold prices follow a continuous uniform distribution. What is the probability that the price will be less than $1,600 three years from now?

Solution:

F(1,600) = \frac{1600 - 1500}{1700 - 1500} = 50\% . The probability that gold price will be less than $1,600 per ounce three years from now is 50%.

 


Quantitative Methods Common Probability Distributions Part 2