The Binomial Distribution For the very common case of “Either-Or” experiments with only two possible outcomes.

Slides:



Advertisements
Similar presentations
HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Section 5.2.
Advertisements

Chapter 7 Discrete Distributions. Random Variable - A numerical variable whose value depends on the outcome of a chance experiment.
Section 5.2 The Binomial Distribution
The Geometric Distributions Section Starter Fred Funk hits his tee shots straight most of the time. In fact, last year he put 78% of his.
Section 5.1 Random Variables
Binomial Probability Distributions
Binomial Probability Distribution
Binomial Distribution. Recall that for a binomial distribution, we must have: Two possible outcomes, called success and failure Constant probability Independent.
Kate Schwartz & Lexy Ellingwood CHAPTER 8 REVIEW: THE BINOMIAL AND GEOMETRIC DISTRIBUTIONS.
Binomial PDF and CDF Section Starter Five marbles are on a table. Two of them are going to be painted with a “W” and the rest will be painted.
HAWKES LEARNING SYSTEMS Students Matter. Success Counts. Copyright © 2013 by Hawkes Learning Systems/Quant Systems, Inc. All rights reserved. Section 5.2.
Lesson 6 – 2b Hyper-Geometric Probability Distribution.
Binomial Distibutions Target Goal: I can determine if the conditions for a binomial random variable are met. I can find the individual and cumulative binomial.
Lesson 8 – R Taken from And modified slightlyhttp://
Notes – Chapter 17 Binomial & Geometric Distributions.
1 Chapter 8: The Binomial and Geometric Distributions 8.1Binomial Distributions 8.2Geometric Distributions.
AP Statistics Powerpoint created, constructed, mocked, fabricated, completed, assembled, pondered, built, produced, made, contrived, conceived, actualized,
Section 5-3 Binomial Probability Distributions. BINOMIAL PROBABILITY DISTRTIBUTION 1.The procedure has a fixed number of trials. 2.The trials must be.
The Practice of Statistics Third Edition Chapter 8: The Binomial and Geometric Distributions Copyright © 2008 by W. H. Freeman & Company Daniel S. Yates.
Binomial Probability Distribution
Binomial Probability Distributions
The Binomial Distribution
There are 4 runners on the New High School team
1 Chapter 4. Section 4-3. Triola, Elementary Statistics, Eighth Edition. Copyright Addison Wesley Longman M ARIO F. T RIOLA E IGHTH E DITION E LEMENTARY.
Section 5.2 Binomial Distribution HAWKES LEARNING SYSTEMS math courseware specialists Copyright © 2008 by Hawkes Learning Systems/Quant Systems, Inc. All.
Math Tech IIII, May 4 The Binomial Distribution IV Book Sections: 4.2 Essential Questions: How can I compute the probability of any event? What do I need.
Dan Piett STAT West Virginia University Lecture 5.
Lesson Discrete Distribution Binomial Taken from
The Binomial Distribution
The Binomial & Geometric Distribution
8.1 The Binomial Distribution
Ch. 15H continued. * -applied to experiments with replacement ONLY(therefore…..independent events only) * -Note: For DEPENDENT events we use the “hypergeometric.
Lesson 6 – 2c Negative Binomial Probability Distribution.
There are 4 runners on the New High School team. The team is planning to participate in a race in which each runner runs a mile. The team time is the sum.
Copyright © 2010 Pearson Education, Inc. Chapter 17 Probability Models.
Probability Distributions, Discrete Random Variables
AP Statistics Monday, 30 November 2015 OBJECTIVE TSW begin the study of discrete distributions. EVERYONE needs a calculator. The tests are graded.
The Practice of Statistics Third Edition Chapter 8: The Binomial and Geometric Distributions Copyright © 2008 by W. H. Freeman & Company Daniel S. Yates.
Section 6.3 Second Day Binomial Calculations on the TI µ and σ of a Binomial RV.
Chapter 8 The Binomial & Geometric Distributions.
Prob and Stats, Oct 28 The Binomial Distribution III Book Sections: N/A Essential Questions: How can I compute the probability of any event? How can I.
Objective: Objective: To solve multistep probability tasks with the concept of binomial distribution CHS Statistics.
Geometric Distribution. The geometric distribution computes the probability that the first success of a Bernoulli trial comes on the kth trial. For example,
Notes – Chapter 17 Binomial & Geometric Distributions.
Chapter 3 Discrete Random Variables and Probability Distributions  Random Variables.2 - Probability Distributions for Discrete Random Variables.3.
The Variance of a Random Variable Lecture 35 Section Fri, Mar 26, 2004.
Lesson The Normal Approximation to the Binomial Probability Distribution.
Lesson 6.3 Discrete Distribution Binomial. Knowledge Objectives Describe the conditions that need to be present to have a binomial setting. Define a binomial.
Unit 4 Review. Starter Write the characteristics of the binomial setting. What is the difference between the binomial setting and the geometric setting?
Binomial Distribution. First we review Bernoulli trials--these trial all have three characteristics in common. There must be: Two possible outcomes, called.
Section 6.3 Day 1 Binomial Distributions. A Gaggle of Girls Let’s use simulation to find the probability that a couple who has three children has all.
Calculating Binomial Probability Exactly – Binompdf At most – Binomcdf At least - “1 – “
+ Binomial and Geometric Random Variables Textbook Section 6.3.
Copyright © 2009 Pearson Education, Inc. Chapter 17 Probability Models.
7.4 and 7.5 Obj: Assess normality of a distribution and find the normal approximation to a binomial distribution.
Lesson Discrete Distribution Binomial. Knowledge Objectives Describe the conditions that need to be present to have a binomial setting. Define a.
Chapter 6 Normal Approximation to Binomial Lecture 4 Section: 6.6.
Continuous vs. Discrete
Section 6.2 Binomial Distribution
Bernoulli Trials and Binomial Probability models
Geometric Distribution
Quiz 6.1 – 6.2 tomorrow Test 6.1 – 6.2 on Monday
Probability 5: Binomial Distribution
Special Discrete Distributions
Section 6.2 Binomial Probability Distribution
Probability Review for Financial Engineers
Discrete Distributions
Elementary Statistics
The Poisson Distribution
Review of Chapter 8 Discrete PDFs Binomial and Geometeric
Presentation transcript:

The Binomial Distribution For the very common case of “Either-Or” experiments with only two possible outcomes

Recognize Binomial Situations

A special kind of probability distribution OutcomesProbabilities One of the events The other event TotalExactly 1

The Binomial Probability Formula

Practice with the Formula

Summary of the 7-11 experiment X successesP(X successes) 0 times (no sevens or elevens) 1 time 2 times 3 times 4 times 5 times (all sevens and elevens) Total (must equal !!)

Sometimes you add probabilities Probability of at least three wins in five trials – P(X≥3) = P(X=3) + P(X=4) + P(X=5) add them up! Probability of more than three wins – P(X>3) = P(X=4) + P(X=5) Probability of at most three wins – P(X≤3) = P(X=0) + P(X=1) + P(X=2) + P(X=3) Probability of fewer than three wins – P(X<3) = P(X=0) + P(X=1) + P(X=2)

Use the Complement to save time

TI-84 Computations

binomcdf(n, p, x) = P(X=0) + P(X=1) + … P(X=x) successes in n trials binomcdf(n, p, x) does lots of little binompdf() for you for x = 0, x = 1, etc. up to the x you told it, and it adds up the results The “cdf” in “binomcdf” stands for “cumulative distribution function”

Try and verify binomcdf(n,p,x) X successesP(X successes) Using binompdf P(0 thru X) successes Using binomcdf 0 times (no sevens or elevens) 1 time 2 times 3 times 4 times 5 times (all sevens and elevens) Total (must equal !!)

binomcdf() and complements Sevens or elevens, n = 50 trials again P(no more than 10 successes) – binomcdf(50, 8/36, 10) P(fewer than 10 successes) – binomcdf(50, 8/36, 9) P(more than 10 successes) – use complement! – 1 minus binomcdf(50, 8/36, 10) P(at least 10 successes) – use complement! – 1 minus binomcdf(50, 8/36, 9)

Mean, Variance, and Standard Deviation

Standard Deviation What happens to the standard deviation in the seven-eleven experiment as the number of trials, n, increases?

Advanced TI-84 Exercise Y 1 =binompdf(20,8/36,X) seq(X,X,0,20) STO> L 1 seq(Y 1 (X),X,0,20) STO> L 2 STAT PLOT for these two lists, histogram WINDOW Xmin=0, Xmax=20, Ymin=-0.1,Ymax=0.6 ZOOM 9:ZoomStat