Chapter 7 Section 5.  Binomial Distribution required just two outcomes (success or failure).  Multinomial Distribution can be used when there are more.

Slides:

Advertisements

Similar presentations

Probability Distribution

Advertisements

MOMENT GENERATING FUNCTION AND STATISTICAL DISTRIBUTIONS

Chapter 12 Probability © 2008 Pearson Addison-Wesley. All rights reserved.

HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Section 5.4.

Statistics Chapter 3: Introduction to Discrete Random Variables.

Probability Sample Space Diagrams.

Discrete Probability Distributions Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing.

Today Today: Finish Chapter 3, begin Chapter 4 Reading: –Have done –Please start reading Chapter 4 –Suggested problems: 3.24, 4.2, 4.8, 4.10, 4.33,

Discrete Probability Distributions

13-4 Compound Probability

Discrete Probability Distributions

5-3 Binomial Probability Distributions

Discrete Probability Distributions

Binomial Probability Distribution

Find the mean & St. Dev for each. MeanSt. Dev X83 Y124.

Lesson 6 – 2b Hyper-Geometric Probability Distribution.

Binomial & Geometric Random Variables §6-3. Goals: Binomial settings and binomial random variables Binomial probabilities Mean and standard deviation.

Chapter 12 Section 5 - Slide 1 Copyright © 2009 Pearson Education, Inc. AND.

Section 15.8 The Binomial Distribution. A binomial distribution is a discrete distribution defined by two parameters: The number of trials, n The probability.

Section Copyright © 2014, 2012, 2010 Pearson Education, Inc. Lecture Slides Elementary Statistics Twelfth Edition and the Triola Statistics Series.

Binomial Distributions Introduction. There are 4 properties for a Binomial Distribution 1. Fixed number of trials (n) Throwing a dart till you get a bulls.

Math 409/409G History of Mathematics

Copyright © 2009 Pearson Education, Inc. Chapter 12 Section 11 - Slide 1 P-10 Probability Binomial Probability Formula.

Copyright © 2015 The McGraw-Hill Companies, Inc. Permission required for reproduction or display. 1 C H A P T E R F I V E Discrete Probability Distributions.

Chapter 7 Lesson 7.5 Random Variables and Probability Distributions

6.4 Find Probabilities of Compound Events Example 1 Find the probability of A or B You randomly choose a card from a standard deck of 52 playing cards.

Binomial Probability Distribution

Probability Definitions Dr. Dan Gilbert Associate Professor Tennessee Wesleyan College.

Chapter 12 Probability. Chapter 12 The probability of an occurrence is written as P(A) and is equal to.

Chapter 9 Review. 1. Give the probability of each outcome.

Math b (Discrete) Random Variables, Binomial Distribution.

Algebra II 10.4: Find Probabilities of Disjoint and Overlapping Events HW: HW: p.710 (8 – 38 even) Chapter 10 Test: Thursday.

Chapter 4 Probability. Definitions A probability experiment is a chance process that leads to well-defined results called outcomes. An outcome is the.

EXAMPLE 3 Find the probability of A and B You take a city bus from your neighborhood to a location within walking distance of your school. The express.

Copyright 2013, 2010, 2007, Pearson, Education, Inc. Section Binomial Probability Formula.

Example Suppose we roll a die and flip a coin. How many possible outcomes are there? Give the sample space. A and B are defined as: A={Die is a 5 or 6}

4.3 More Discrete Probability Distributions NOTES Coach Bridges.

Chapter 12 Section 1 - Slide 1 Copyright © 2009 Pearson Education, Inc. AND.

6.2 BINOMIAL PROBABILITIES.  Features  Fixed number of trials (n)  Trials are independent and repeated under identical conditions  Each trial has.

Chapter 12 Section 5 - Slide 1 Copyright © 2009 Pearson Education, Inc. AND.

Binomial Probability Distribution

Copyright © 2010, 2007, 2004 Pearson Education, Inc. Lecture Slides Elementary Statistics Eleventh Edition and the Triola Statistics Series by.

Special Discrete Distributions: Geometric Distributions.

Pre-Algebra 9-7 Independent and Dependent Events Learn to find the probabilities of independent and dependent events.

Chapter 7 Sets & Probability Section 7.3 Introduction to Probability.

Discrete Probability Distributions Chapter 4. § 4.3 More Discrete Probability Distributions.

Copyright © 2009 Pearson Education, Inc. Chapter 12 Section 6 - Slide 1 Section 6 Or and And Problems.

DO NOW 4/27/2016 Find the theoretical probability of each outcome. 1. rolling a 6 on a number cube. 2. rolling an odd number on a number cube. 3. flipping.

AP Statistics Chapter 8 Section 2. If you want to know the number of successes in a fixed number of trials, then we have a binomial setting. If you want.

Combinatorial Principles, Permutations, and Combinations

Ch3.5 Hypergeometric Distribution

Probability Probability is a measure of how likely it is that an event will occur. Probability can be expressed as a fraction, decimal, or percent.

Introduction to probability (5)

6.4 Find Probabilities of Compound Events

Discrete Probability Distributions

Lesson 13.4 Find Probabilities of Compound Events

Quote of the Day It is a mathematical fact that the casting of this pebble from m hand alters the centre of gravity of the universe. -Thomas Carlyle.

Discrete Probability Distributions

Probability Models Section 6.2.

Statistics 1: Elementary Statistics

The Binomial and Geometric Distributions

Statistics 1: Elementary Statistics

Section 3: Estimating p in a binomial distribution

Section 11.7 Probability.

Section 14.5 – Independent vs. Dependent Events

Elementary Statistics

Bernoulli Trials Two Possible Outcomes Trials are independent.

The Geometric Distributions

Chapter 11 Probability.

Presentation transcript:

Chapter 7 Section 5

 Binomial Distribution required just two outcomes (success or failure).  Multinomial Distribution can be used when there are more than two possible outcomes  Conditions are the same as binomial distribution (outcomes independent, fixed number of trials, probabilities must remain constant, and events must be mutually exclusive.)

If X consists of events which have corresponding probabilities of occurring and is the number of times will occur, is the number of times will occur, etc, then the probability that X will occur is where and

In a large city, 50% of people choose a movie, 30% choose dinner and a play, and 20% choose shopping as a leisure activity. If a sample of 5 people is randomly selected, find the probability that 3 are planning to go to a movie, 1 to a play, and 1 to a shopping mall.

A box contains 4 white balls, 3 red balls, and 3 blue balls. A ball is selected at random and it’s color is written down. It is replaced each time. Find the probability that if 5 balls are selected, 2 are white, 2 are red, and 1 is blue.