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.

Slides:



Advertisements
Similar presentations
Probability Distribution
Advertisements

If X has the binomial distribution with n trials and probability p of success on each trial, then possible values of X are 0, 1, 2…n. If k is any one of.
Lesson Objective Be able to calculate probabilities for Binomial situations Begin to recognise the conditions necessary for a Random variable to have a.
Chapter 12 Probability © 2008 Pearson Addison-Wesley. All rights reserved.
Problems Problems 4.17, 4.36, 4.40, (TRY: 4.43). 4. Random Variables A random variable is a way of recording a quantitative variable of a random experiment.
Monopoly Game Example Mutually Exclusive.
Unit 5 Section : The Binomial Distribution  Situations that can be reduces to two outcomes are known as binomial experiments.  Binomial experiments.
5.1 Sampling Distributions for Counts and Proportions.
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
Binomial Distributions. Binomial Experiments Have a fixed number of trials Each trial has tow possible outcomes The trials are independent The probability.
Chapter 5 Section 2: Binomial Probabilities. trial – each time the basic experiment is performed.
CHAPTER 8_A PROBABILITY MODELS BERNOULLI TRIAL
The Binomial Distribution. Introduction # correct TallyFrequencyP(experiment)P(theory) Mix the cards, select one & guess the type. Repeat 3 times.
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.
Binomial & Geometric Random Variables §6-3. Goals: Binomial settings and binomial random variables Binomial probabilities Mean and standard deviation.
Section 15.8 The Binomial Distribution. A binomial distribution is a discrete distribution defined by two parameters: The number of trials, n The probability.
Binomial distribution Nutan S. Mishra Department of Mathematics and Statistics University of South Alabama.
Statistics 1: Elementary Statistics Section 5-4. Review of the Requirements for a Binomial Distribution Fixed number of trials All trials are independent.
Binomial Distributions Calculating the Probability of Success.
The Binomial Distribution. Binomial Experiment.
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
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.
King Saud University Women Students
The Binomial Distribution
4.2 Binomial Distributions
Statistics 3502/6304 Prof. Eric A. Suess Chapter 4.
Lecture 9 The Binomial Distribution Math 1107 Introduction to Statistics.
6.2 BINOMIAL PROBABILITIES.  Features  Fixed number of trials (n)  Trials are independent and repeated under identical conditions  Each trial has.
Binomial Distribution Memory trick. bi no mi al.
This is a discrete distribution. Situations that can be modeled with the binomial distribution must have these 4 properties: Only two possible outcomes.
Binomial Formula. There is a Formula for Finding the Number of Orderings - involves FACTORIALS.
Binomial Probability A Binomial Probability experiment has the following features.  There is a fixed number of repeated trials.  Each trial has two.
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.
Special Discrete Distributions: Geometric Distributions.
6.2 Binomial Distributions Recognize and calculate probabilities that are binomial distributions Use the probabilities and expected values to make decision.
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.
Multinomial Distribution World Premier League Soccer Game Outcomes.
1. Binomial Trials: Success/Failure 2. Probability of k Successes 1.
MATH 2311 Section 3.3.
Binomial Distribution. Bernoulli Trials Repeated identical trials are called Bernoulli trials if: 1. There are two possible outcomes for each trial, denoted.
Starter Toss the two coins and record the results two heads a head and a tail two tails P(two heads) P(a head and a tail) P(two tails)
Binomial Distribution Introduction: Binomial distribution has only two outcomes or can be reduced to two outcomes. There are a lot of examples in engineering.
The binomial distribution
Binomial Distribution
MATH 2311 Section 3.3.
Negative Binomial Experiment
3.4 The Binomial Distribution
Statistics 1: Elementary Statistics
Lesson 2: Binomial Distribution
Discrete Probability Distribution
Binomial Distribution
Statistics 1: Elementary Statistics
Binomial Distribution
If the question asks: “Find the probability if...”
MATH 2311 Section 3.3.
Bernoulli Trials Two Possible Outcomes Trials are independent.
Bernoulli Trials and The Binomial Distribution
Binomial Distributions
STARTER P = 2A + 3B E(P) = 2 x x 25 = 135
Binomial Distribution
MATH 2311 Section 3.3.
Chapter 11 Probability.
Applied Statistical and Optimization Models
Presentation transcript:

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 eye

There are 4 properties for a Binomial Distribution 1. Fixed number of trials (n) Playing two soccer matches 2. Two outcomes in a trial, success or failure

There are 4 properties for a Binomial Distribution 1. Fixed number of trials (n) 2. Two outcomes in a trial, success or failure Playing two games of tennis 3. Trials are independent

There are 4 properties for a Binomial Distribution 1. Fixed number of trials (n) 2. Two outcomes in a trial, success or failure 3. Trials are independent Throwing a die and spinning a coin 4. Probability of success (p) remains constant

There are 4 properties for a Binomial Distribution 1. Fixed number of trials (n) 2. Two outcomes in a trial, success or failure 3. Trials are independent 4. Probability of success (p) remains constant