Presentation Overview

The slide covers comprehensive content on <p>&bull;The <strong>binomial probability distribution </strong>is one of the most widely used discrete probability distributions.</p> <p>&bull;It is applied to find the probability that an outcome will occur <em>x </em>times in n performances of an experiment.</p> <p>&bull;For example, given that the probability is .05 that a DVD player manufactured at a firm is defective, we may be interested in finding the probability that in a random sample of three DVD players manufactured at this firm, exactly one will be defective.</p> <p>&bull;To apply the binomial probability distribution, the random variable <em>x must be a discrete </em>dichotomous random variable.</p> <p>&bull;In other words, the variable must be a discrete random variable, and each repetition of the experiment must result in one of two possible outcomes.</p> <p>&bull;The binomial distribution is applied to experiments that satisfy the four conditions of a <em>binomial experiment</em></p> <p>&bull;Each repetition of a binomial experiment is called a <strong>trial or a Bernoulli trial </strong>(after Jacob Bernoulli).</p> <p>&bull;For example, if an experiment is defined as one toss of a coin and this experiment is repeated 10 times, then each repetition (toss) is called a trial.</p> <p>&bull;Consequently, there are 10 total trials for this experiment.</p> . You can play the slide in our in-built slide player or download for offline reading.