lecture4

# lecture4 - Cumulative Binomial Probabilities • Recall...

This preview shows pages 1–4. Sign up to view the full content.

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document

This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Cumulative Binomial Probabilities • Recall Binomial random variable: 1. an experiment consisting of n indepen- dent identical trials, say n = 20; 2. depends on a parameter p , the success probability; 3. counting the number of successes. • Usually denoted by X ∼ Binomial ( n,p ). 1 • How do we describe a discrete random vari- able? Use mass function p ( x ) := P ( X = x ) . • For X ∼ Binomial (20 ,. 6), what is its mass function p ( x )? p ( x ) = 20 x (0 . 6) x (0 . 4) 20- x where 20 x = 20! x !(20- x )! and x ! = 1 * 2 * 3 ··· x . 2 Table II on page 785 • Because of the significance of Binomial dis- tributions, their mass functions are usually well known and very well tabulated. • Those listed values are cumulative proba- bilities, P ( X ≤ k ) = P ( X = 1) + ··· + P ( X = k ) . • Remark: Knowing mass function is equiv- alent to knowing cumulative probabilities....
View Full Document

{[ snackBarMessage ]}

### Page1 / 11

lecture4 - Cumulative Binomial Probabilities • Recall...

This preview shows document pages 1 - 4. Sign up to view the full document.

View Full Document
Ask a homework question - tutors are online