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1. The probability of success remains constant from trial to trial in a binomial experiment. 2. In a multinomial experiment, the number of outcomes per trial is more than two and the probability of success of outcomes remains constant per trial. 3. The mean (expected value) and variance of a Poisson random variable are both equal to the average rate of occurrence A.

1. The probability of success remains constant from trial to trial in a binomial experiment. 2. In a multinomial experiment, the number of outcomes per trial is more than two and the probability of success of outcomes remains constant per trial. 3. The mean (expected value) and variance of a Poisson random variable are both equal to the average rate of occurrence A.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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TRUE OR FALSE 1. The probability of success remains constant from trial to trial in a binomial experiment. 2. In a multinomial experiment, the number of outcomes per trial is more than two and the probability of success of outcomes remains constant per trial. 3. The mean (expected value) and variance of a Poisson random variable are both equal to the average rate of occurrence A. 4. A normal distribution is a positively skewed distribution that is unimodal and asymptotic with respect to x-axis. 5. A normal random variable X can be transformed into its standard form Z using the formula Z = (x-μ)/σ which follows the standard normal distribution with mean equal to 0 and variance equal to 1.
Transcribed Image Text:TRUE OR FALSE 1. The probability of success remains constant from trial to trial in a binomial experiment. 2. In a multinomial experiment, the number of outcomes per trial is more than two and the probability of success of outcomes remains constant per trial. 3. The mean (expected value) and variance of a Poisson random variable are both equal to the average rate of occurrence A. 4. A normal distribution is a positively skewed distribution that is unimodal and asymptotic with respect to x-axis. 5. A normal random variable X can be transformed into its standard form Z using the formula Z = (x-μ)/σ which follows the standard normal distribution with mean equal to 0 and variance equal to 1.
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