University:
Everett Community College
Course:
MATH 146 | Introduction to Statistics
Academic year:

2015
Views:

487

Pages:

2
Author:

Tianna Jacobson

Binomial and Normal Probability Distribution TI 83/84 Binomial Distribution TI 83/84 Parameters: n = number of trials, p = probability of success, x = number of successes Example Successes = 5 Calculator To calculate the binomial probability for exactly one particular number of successes P( x = 5) binompdf(n ,p, x) binompdf(n, p, 5) from example To calculate the binomial probability of at most any number of successes P( x < 5 ) binomcdf(n, p, x) binomcdf(n, p, 5) from example To calculate the binomial probability of fewer than any number of successes P( x < 5 ) Note: Does not include 5 binomcdf(n, p, x) binomcdf(n, p, 4) from example To calculate the binomial probability of more than any number of successes P( x > 5 ) = 1 – P( x < 5 ) Think complement 1 – binomcdf(n, p, x) 1 – binomcdf(n, p, 5) from example To calculate the binomial probability of at least any number of successes P( x > 5 ) = 1 – P(x < 4) Think complement 1 – binomcdf(n, p, x) 1 – binomcdf(n, p, 4) from example Normal Distribution TI 83/84 Have Boundaries – Need Area Have Area – Need Boundary Working with z scores normalcdf(left boundary, right boundary) invNorm(area to the left) Working with raw (x) scores normalcdf(left boundary, right boundary ,mean, std deviation) invNorm(area to the left, mean, std deviation)

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