MATH221 Discrete Probability Variables

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MATH221 Discrete Probability Variables
For this discussion you will use technology to create a short 1-2 minute multimedia post/presentation…

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MATH221 Discrete Probability Variables

MATH221 Discrete Probability Variables

Discussions Week 3 All Students Posts 60 Pages

For this discussion you will use technology to create a short 1-2 minute multimedia post/presentation.

Suggestions: Narrated PowerPoint, recorded video (.mp4), Screencast-O-Matic (.mp4), or a similar tool of your choice. Video can be recorded directly within a post as well, but make sure to plan out in advance what you are going to say/show. There should be a visual component as well as audio, so if you are using a webcam for the video that only shows you speaking, please attach your PowerPoint slide(s) (or screenshot images of them) to the post as well so everyone can see them.

In your short presentation, you will be describing an example that uses discrete probabilities or distributions. Provide an example that follows either the binomial probabilities or any discrete probability distribution, and explain why that example follows that distribution. In your responses to other students, make up numbers for the example provided by that other student, and ask a related probability question. Then show the work (or describe the technology steps) and solve that probability example.

For more information about Narrated PowerPoint, access the Student Resources section of Course Resources under the Introduction & Resources module heading, and look for the heading that corresponds to the tool you want to use. For all media posts in this course, please include a brief written synopsis to inform your classmates what the main point or purpose is that the linked, attached, or embedded media addresses.

We need to  meet two conditions for a distribution to be considered a probability distribution.

  1. a) All probabilities have to be between 0 and 1,
  2. b) Sum of all probabilities has to be 1.

There are three characteristics of a binomial experiment:

  1. There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter ndenotes the number of trials.
  2. There are only two possible outcomes, called successand failure, for each trial. The outcome that we are measuring is defined as a success, while the other outcome is defined as a failure. The letter p denotes the probability of a success on one trial, and q denotes the probability of a failure on one trial. p + q = 1.
  3. The ntrials are independent and are repeated using identical conditions. Because the n trials are independent, the outcome of one trial does not help in predicting the outcome of another trial. Another way of saying this is that for each individual trial, the probability, p, of a success and probability, q, of a failure remain the same. Let us look at several examples of a binomial experiment…