Binomial Distribution

Slides:



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

Unit 18 Section 18C The Binomial Distribution. Example 1: If a coin is tossed 3 times, what is the probability of obtaining exactly 2 heads Solution:
5.1 Sampling Distributions for Counts and Proportions.
Chapter 5 Probability Distributions
CHAPTER 8_A PROBABILITY MODELS BERNOULLI TRIAL
1 Binomial Probability Distribution Here we study a special discrete PD (PD will stand for Probability Distribution) known as the Binomial PD.
Discrete Random Variables: The Binomial Distribution
Quiz 4  Probability Distributions. 1. In families of three children what is the mean number of girls (assuming P(girl)=0.500)? a) 1 b) 1.5 c) 2 d) 2.5.
Construction Engineering 221 Statistics and Probability Binomial Distribution Part II.
Binomial & Geometric Random Variables §6-3. Goals: Binomial settings and binomial random variables Binomial probabilities Mean and standard deviation.
6.2 – Binomial Probabilities You are at your ACT test, you have 3 problems left to do in 5 seconds. You decide to guess on all three, since you don't have.
Section 15.8 The Binomial Distribution. A binomial distribution is a discrete distribution defined by two parameters: The number of trials, n The probability.
Thermo & Stat Mech - Spring 2006 Class 16 More Discussion of the Binomial Distribution: Comments & Examples jl.
Statistics 1: Elementary Statistics Section 5-4. Review of the Requirements for a Binomial Distribution Fixed number of trials All trials are independent.
Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics Statistics & Econometrics.
Binomial Distributions Calculating the Probability of Success.
The Binomial Distribution. Binomial Experiment.
Business and Finance College Principles of Statistics Eng. Heba Hamad 2008.
1 Bernoulli trial and binomial distribution Bernoulli trialBinomial distribution x (# H) 01 P(x)P(x)P(x)P(x)(1 – p)p ?
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.
Discrete Probability Distributions
Simple Mathematical Facts for Lecture 1. Conditional Probabilities Given an event has occurred, the conditional probability that another event occurs.
Copyright © 1998, Triola, Elementary Statistics Addison Wesley Longman 1 Binomial Experiments Section 4-3 & Section 4-4 M A R I O F. T R I O L A Copyright.
Bernoulli Trials Two Possible Outcomes –Success, with probability p –Failure, with probability q = 1  p Trials are independent.
Aim: How do we use binomial probability? Complete worksheet.
Binomial Experiment A binomial experiment (also known as a Bernoulli trial) is a statistical experiment that has the following properties:
Binomial Probability Distribution
Probability Distributions BINOMIAL DISTRIBUTION. Binomial Trials There are a specified number of repeated, independent trials There are a specified number.
Binomial Distributions. Quality Control engineers use the concepts of binomial testing extensively in their examinations. An item, when tested, has only.
COMP 170 L2 L17: Random Variables and Expectation Page 1.
4.2 Binomial Distributions
6.2 BINOMIAL PROBABILITIES.  Features  Fixed number of trials (n)  Trials are independent and repeated under identical conditions  Each trial has.
This is a discrete distribution. Situations that can be modeled with the binomial distribution must have these 4 properties: Only two possible outcomes.
Binomial Distribution If you flip a coin 3 times, what is the probability that you will get exactly 1 tails? There is more than one way to do this problem,
Section 9-3 Probability. Probability of an Event if E is an event in a sample space, S, of equally likely outcomes, then the probability of the event.
Chapter 7 Section 5.  Binomial Distribution required just two outcomes (success or failure).  Multinomial Distribution can be used when there are more.
Bernoulli Trials, Geometric and Binomial Probability models.
Chapter 5 Joint Probability Distributions and Random Samples  Jointly Distributed Random Variables.2 - Expected Values, Covariance, and Correlation.3.
6.2 Binomial Distributions Recognize and calculate probabilities that are binomial distributions Use the probabilities and expected values to make decision.
Discrete Math Section 16.3 Use the Binomial Probability theorem to find the probability of a given outcome on repeated independent trials. Flip a coin.
16-3 The Binomial Probability Theorem. Let’s roll a die 3 times Look at the probability of getting a 6 or NOT getting a 6. Let’s make a tree diagram.
When could two experimental probabilities be equal? Question of the day.
Binomial Probability Theorem In a rainy season, there is 60% chance that it will rain on a particular day. What is the probability that there will exactly.
Random Variables Lecture Lecturer : FATEN AL-HUSSAIN.
Introduction to Probability How do we find the theoretical probability of an event?
Binomial Distribution (Dr. Monticino). Assignment Sheet  Read Chapter 15  Assignment # 9 (Due March 30 th )  Chapter 15  Exercise Set A: 1-6  Review.
The binomial distribution
Binomial Distribution
Negative Binomial Experiment
Sec. 4-5: Applying Ratios to Probability
Chapter 5 Joint Probability Distributions and Random Samples
8.1 Normal Approximations
Statistics 1: Elementary Statistics
More Discussion of the Binomial Distribution: Comments & Examples
Probability Trees By Anthony Stones.
The Binomial and Geometric Distributions
The Binomial Distribution
More Discussion of the Binomial Distribution: Comments & Examples
Binomial Distribution
Statistics 1: Elementary Statistics
Binomial Distribution Prof. Welz, Gary OER –
Probability of TWO EVENTS
Bernoulli Trials Two Possible Outcomes Trials are independent.
Probability distributions
Discrete Uniform distributions
Probability Tree Diagrams
Probability Mutually exclusive and exhaustive events
Investigation Write down the sample space for throwing a die and tossing a coin. 1T 2T 3T 4T 5T 6T 1H 2H 3H 4H 5H 6H   From the sample space calculate:
Chapter 11 Probability.
Binomial Distribution
Presentation transcript:

Binomial Distribution GCSE Statistics Binomial Distribution

A binomial distribution occurs when there are a fixed number of independent trials(n), each trial having only two outcomes. Examples of this are heads or tails on a coin, 6 or not 6 on a die, The outcomes are defined as success or failure. The probability of success is p. The probability of failure is q, where q = 1 – p (since p + q = 1) The binomial distribution is written as B(n,p) where n is the number of trials and p is the probability of success. If I flip a coin 20 times the binomial distribution is expressed as B(20, 0.5) or B(20, ½)

The probabilities for the events of n binomial trials are the terms of the expansion (p + q)n so if there are 2 trials we get (p + q)2 = p² + 2pq + q² for 3 trials (p + q)3 = p³ + 3p²q + 3pq² + q³ for 4 trials (p + q)⁴ = p⁴ + 4p³q² + 6p²q² + 4pq³ + q⁴ In the exam you will be expected to deal with values of n up to 2, but will only be expected to remember the expansion for n = 2.

(p + q)⁴ = p⁴ + 4p³q + 6p²q² + 4pq³ + q⁴ For example, the probability of an oboe reed faulty is 0.1 and a packet holds four reeds. You want to find the probability there are one or fewer faulty oboe reeds. You are given that: (p + q)⁴ = p⁴ + 4p³q + 6p²q² + 4pq³ + q⁴ (4 good) (3 good 1 faulty) (2 good 2 faulty) (1 good 3 faulty) (4 faulty) in this case P(success) = 1 – 0.1 = 0.9 q = P(failure) = 0.1 one or fewer faulty reeds are the terms p⁴ + 4p³q² = 0.9⁴ + (4 x 0.9³ x 0.1) = 0.6561 + 0.291 6 = 0.9477 the probability of having one or fewer faulty oboe reeds in a pack is 0.9477 (94.77%)

Your turn Exercise 8c page 300