Probability Notes: Binomial Probabilities

Size: px
Start display at page:

Download "Probability Notes: Binomial Probabilities"

Transcription

1 Probability Notes: Binomial Probabilities A Binomial Probability is a type of discrete probability with only two outcomes (tea or coffee, win or lose, have disease or don t have disease). The category you are finding the percentage of is the success category or in Statcato it is called the event probability. Success Category (have disease) Failure Category (don t have disease) For a binomial probability, individual observations should be independent of each other with a consistent probability of success. (For example, winning at cards often fails this assumption because the number of cards and the probabilities are always changing.) Calculating Binomial Probabilities When calculating binomial probabilities, you need three bits of information. Number of events (successes) (X) Event probability (probability that the success category happens 1 time. (p) Total number of trials (total number of people or total number of times you plan to play the game, sample size) (n) The Binomial formula programmed into computers is this. This calculates only the P(x =#) and has to be repeated over and over to calculate less than or greater than. Lucky computers can handle the computations. PP(XX) = CC(nn, xx) pp xx (1 pp) nn xx

2 Calculate Binomial Probabilities with Statcato Calculate Menu => Probability Distributions => Binomial Enter the total number of people or times played under number of trials Enter the % (as a decimal proportion) for one success under event probability. Enter the number of success (X) under constant Calculate Binomial Probabilities with StatCrunch Stat Menu => Calculator => Binomial => Standard or Between

3 Note about inequality symbols. Normal Probabilities: When dealing with continuous quantitative data with decimals, we had infinite totals so the probability of less than 3 kilograms is or below. Hence for normal probabilities the probability of less than 3 is about the same as less than or equal to. Binomial Probabilities: This is not the case for binomial probabilities. Winning a game less than 3 times means winning less than or equal to 2 times. So be careful about the wording with inequalities. For Binomial calculations in Statcato, probability density finds the % for number of events equal to a #, cumulative probability finds the % for the number of events less than or equal to a #. Remember subtracting the cumulative probability from 100% will give the % for strictly greater than. For Binomial calculations in StatCrunch, you have the options of =, <, >,, Remember greater than points right and less than points left.

4 Wording examples = probability that exactly 5 people have the disease (In statcato, calculate with the probability density function with 5 events.) > probability that she wins more than 4 times (Notice more than 4 means greater than or equal to 5. In Statcato, calculate less than or equal to 4 with the cumulative probability function and subtract the answer from 100%) probability that she wins 4 or more times or at least 4 (In Statcato, calculate less than or equal to 3 with the cumulative probability function and subtract the answer from 100%) < probability that he wins less than 6 times (notice less than 6 means less than or equal to 5. In Statcato, calculate less than or equal to 5 with the cumulative probability function) probability that he wins 6 times or less or at most 6 (In Statcato, calculate less than or equal to 6 with the cumulative probability function)

5 Let s look at some examples. Sarah likes to play slot machines in a Casino in Las Vegas. The particular slot machine she is playing has a 7% chance of winning. Suppose Sarah plays the game 35 total times. 1. What is the probability that Sarah wins exactly 2 times. In Statcato, enter 35 under number of trials, 0.07 under event probability and 2 under constant. We will use the probability density button since we are calculating equal to. So the answer is 26.6%

6 2. What is the probability that Sarah wins more than 3 times? First notice that more than 3 means 4 or more. The opposite of 4 or more is 3 or less. So we will use the cumulative probability button to calculate 3 or less in Statcato. Then subtract the answer from 100%. In Statcato, enter 35 under number of trials, 0.07 under event probability and 3 under constant. Don t forget this calculated the percentage of 3 or less wins not 4 or more. So subtract the answer from 100%. Answer: 100% % = 22.7%

OCR Statistics 1. Discrete random variables. Section 2: The binomial and geometric distributions. When to use the binomial distribution

OCR Statistics 1. Discrete random variables. Section 2: The binomial and geometric distributions. When to use the binomial distribution Discrete random variables Section 2: The binomial and geometric distributions Notes and Examples These notes contain subsections on: When to use the binomial distribution Binomial coefficients Worked examples

More information

Discrete Probability Distributions

Discrete Probability Distributions Chapter 5 Discrete Probability Distributions Goal: To become familiar with how to use Excel 2007/2010 for binomial distributions. Instructions: Open Excel and click on the Stat button in the Quick Access

More information

1 / * / * / * / * / * The mean winnings are $1.80

1 / * / * / * / * / * The mean winnings are $1.80 DISCRETE vs. CONTINUOUS BASIC DEFINITION Continuous = things you measure Discrete = things you count OFFICIAL DEFINITION Continuous data can take on any value including fractions and decimals You can zoom

More information

Binomial Distributions

Binomial Distributions Binomial Distributions (aka Bernouli s Trials) Chapter 8 Binomial Distribution an important class of probability distributions, which occur under the following Binomial Setting (1) There is a number n

More information

Every data set has an average and a standard deviation, given by the following formulas,

Every data set has an average and a standard deviation, given by the following formulas, Discrete Data Sets A data set is any collection of data. For example, the set of test scores on the class s first test would comprise a data set. If we collect a sample from the population we are interested

More information

Math 243 Section 4.3 The Binomial Distribution

Math 243 Section 4.3 The Binomial Distribution Math 243 Section 4.3 The Binomial Distribution Overview Notation for the mean, standard deviation and variance The Binomial Model Bernoulli Trials Notation for the mean, standard deviation and variance

More information

Math 160 Professor Busken Chapter 5 Worksheets

Math 160 Professor Busken Chapter 5 Worksheets Math 160 Professor Busken Chapter 5 Worksheets Name: 1. Find the expected value. Suppose you play a Pick 4 Lotto where you pay 50 to select a sequence of four digits, such as 2118. If you select the same

More information

Discrete Probability Distributions

Discrete Probability Distributions 90 Discrete Probability Distributions Discrete Probability Distributions C H A P T E R 6 Section 6.2 4Example 2 (pg. 00) Constructing a Binomial Probability Distribution In this example, 6% of the human

More information

Lecture 8. The Binomial Distribution. Binomial Distribution. Binomial Distribution. Probability Distributions: Normal and Binomial

Lecture 8. The Binomial Distribution. Binomial Distribution. Binomial Distribution. Probability Distributions: Normal and Binomial Lecture 8 The Binomial Distribution Probability Distributions: Normal and Binomial 1 2 Binomial Distribution >A binomial experiment possesses the following properties. The experiment consists of a fixed

More information

Discrete Probability Distribution

Discrete Probability Distribution 1 Discrete Probability Distribution Key Definitions Discrete Random Variable: Has a countable number of values. This means that each data point is distinct and separate. Continuous Random Variable: Has

More information

Day 2.notebook November 25, Warm Up Are the following probability distributions? If not, explain.

Day 2.notebook November 25, Warm Up Are the following probability distributions? If not, explain. Warm Up Are the following probability distributions? If not, explain. ANSWERS 1. 2. 3. Complete the probability distribution. Hint: Remember what all P(x) add up to? 4. Find the mean and standard deviation.

More information

MA 1125 Lecture 14 - Expected Values. Wednesday, October 4, Objectives: Introduce expected values.

MA 1125 Lecture 14 - Expected Values. Wednesday, October 4, Objectives: Introduce expected values. MA 5 Lecture 4 - Expected Values Wednesday, October 4, 27 Objectives: Introduce expected values.. Means, Variances, and Standard Deviations of Probability Distributions Two classes ago, we computed the

More information

Test 6A AP Statistics Name:

Test 6A AP Statistics Name: Test 6A AP Statistics Name: Part 1: Multiple Choice. Circle the letter corresponding to the best answer. 1. A marketing survey compiled data on the number of personal computers in households. If X = the

More information

MATH 227 CP 6 SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question.

MATH 227 CP 6 SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question. MATH 227 CP 6 SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question. Identify the given random variable as being discrete or continuous. 1) The number of phone

More information

Chapter 2: Categorical & Quantitative Data Analysis

Chapter 2: Categorical & Quantitative Data Analysis Chapter 2: Categorical & Quantitative Data Analysis Vocabulary Data: Information in all forms. Categorical data: Also called qualitative data. Data in the form of labels that tell us something about the

More information

Discrete Probability Distributions

Discrete Probability Distributions Page 1 of 6 Discrete Probability Distributions In order to study inferential statistics, we need to combine the concepts from descriptive statistics and probability. This combination makes up the basics

More information

Chapter 5: Probability models

Chapter 5: Probability models Chapter 5: Probability models 1. Random variables: a) Idea. b) Discrete and continuous variables. c) The probability function (density) and the distribution function. d) Mean and variance of a random variable.

More information

VIDEO 1. A random variable is a quantity whose value depends on chance, for example, the outcome when a die is rolled.

VIDEO 1. A random variable is a quantity whose value depends on chance, for example, the outcome when a die is rolled. Part 1: Probability Distributions VIDEO 1 Name: 11-10 Probability and Binomial Distributions A random variable is a quantity whose value depends on chance, for example, the outcome when a die is rolled.

More information

Problem Set 07 Discrete Random Variables

Problem Set 07 Discrete Random Variables Name Problem Set 07 Discrete Random Variables MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Find the mean of the random variable. 1) The random

More information

Discrete Random Variables and Their Probability Distributions

Discrete Random Variables and Their Probability Distributions 58 Chapter 5 Discrete Random Variables and Their Probability Distributions Discrete Random Variables and Their Probability Distributions Chapter 5 Section 5.6 Example 5-18, pg. 213 Calculating a Binomial

More information

Mean, Variance, and Expectation. Mean

Mean, Variance, and Expectation. Mean 3 Mean, Variance, and Expectation The mean, variance, and standard deviation for a probability distribution are computed differently from the mean, variance, and standard deviation for samples. This section

More information

Statistical Methods in Practice STAT/MATH 3379

Statistical Methods in Practice STAT/MATH 3379 Statistical Methods in Practice STAT/MATH 3379 Dr. A. B. W. Manage Associate Professor of Mathematics & Statistics Department of Mathematics & Statistics Sam Houston State University Overview 6.1 Discrete

More information

What do you think "Binomial" involves?

What do you think Binomial involves? Learning Goals: * Define a binomial experiment (Bernoulli Trials). * Applying the binomial formula to solve problems. * Determine the expected value of a Binomial Distribution What do you think "Binomial"

More information

Objective: To understand similarities and differences between geometric and binomial scenarios and to solve problems related to these scenarios.

Objective: To understand similarities and differences between geometric and binomial scenarios and to solve problems related to these scenarios. AP Statistics: Geometric and Binomial Scenarios Objective: To understand similarities and differences between geometric and binomial scenarios and to solve problems related to these scenarios. Everything

More information

One Proportion Superiority by a Margin Tests

One Proportion Superiority by a Margin Tests Chapter 512 One Proportion Superiority by a Margin Tests Introduction This procedure computes confidence limits and superiority by a margin hypothesis tests for a single proportion. For example, you might

More information

Section 7.5 The Normal Distribution. Section 7.6 Application of the Normal Distribution

Section 7.5 The Normal Distribution. Section 7.6 Application of the Normal Distribution Section 7.6 Application of the Normal Distribution A random variable that may take on infinitely many values is called a continuous random variable. A continuous probability distribution is defined by

More information

GEK1544 The Mathematics of Games Suggested Solutions to Tutorial 3

GEK1544 The Mathematics of Games Suggested Solutions to Tutorial 3 GEK544 The Mathematics of Games Suggested Solutions to Tutorial 3. Consider a Las Vegas roulette wheel with a bet of $5 on black (payoff = : ) and a bet of $ on the specific group of 4 (e.g. 3, 4, 6, 7

More information

Central Limit Theorem 11/08/2005

Central Limit Theorem 11/08/2005 Central Limit Theorem 11/08/2005 A More General Central Limit Theorem Theorem. Let X 1, X 2,..., X n,... be a sequence of independent discrete random variables, and let S n = X 1 + X 2 + + X n. For each

More information

Binomial Probability

Binomial Probability Binomial Probability Features of a Binomial Experiment 1. There are a fixed number of trials. We denote this number by the letter n. Features of a Binomial Experiment 2. The n trials are independent and

More information

guessing Bluman, Chapter 5 2

guessing Bluman, Chapter 5 2 Bluman, Chapter 5 1 guessing Suppose there is multiple choice quiz on a subject you don t know anything about. 15 th Century Russian Literature; Nuclear physics etc. You have to guess on every question.

More information

Chapter 14 - Random Variables

Chapter 14 - Random Variables Chapter 14 - Random Variables October 29, 2014 There are many scenarios where probabilities are used to determine risk factors. Examples include Insurance, Casino, Lottery, Business, Medical, and other

More information

Probability Theory. Mohamed I. Riffi. Islamic University of Gaza

Probability Theory. Mohamed I. Riffi. Islamic University of Gaza Probability Theory Mohamed I. Riffi Islamic University of Gaza Table of contents 1. Chapter 2 Discrete Distributions The binomial distribution 1 Chapter 2 Discrete Distributions Bernoulli trials and the

More information

4: Probability. Notes: Range of possible probabilities: Probabilities can be no less than 0% and no more than 100% (of course).

4: Probability. Notes: Range of possible probabilities: Probabilities can be no less than 0% and no more than 100% (of course). 4: Probability What is probability? The probability of an event is its relative frequency (proportion) in the population. An event that happens half the time (such as a head showing up on the flip of a

More information

STOR 155 Introductory Statistics (Chap 5) Lecture 14: Sampling Distributions for Counts and Proportions

STOR 155 Introductory Statistics (Chap 5) Lecture 14: Sampling Distributions for Counts and Proportions The UNIVERSITY of NORTH CAROLINA at CHAPEL HILL STOR 155 Introductory Statistics (Chap 5) Lecture 14: Sampling Distributions for Counts and Proportions 5/31/11 Lecture 14 1 Statistic & Its Sampling Distribution

More information

Section M Discrete Probability Distribution

Section M Discrete Probability Distribution Section M Discrete Probability Distribution A random variable is a numerical measure of the outcome of a probability experiment, so its value is determined by chance. Random variables are typically denoted

More information

MATH1215: Mathematical Thinking Sec. 08 Spring Worksheet 9: Solution. x P(x)

MATH1215: Mathematical Thinking Sec. 08 Spring Worksheet 9: Solution. x P(x) N. Name: MATH: Mathematical Thinking Sec. 08 Spring 0 Worksheet 9: Solution Problem Compute the expected value of this probability distribution: x 3 8 0 3 P(x) 0. 0.0 0.3 0. Clearly, a value is missing

More information

MA 1125 Lecture 12 - Mean and Standard Deviation for the Binomial Distribution. Objectives: Mean and standard deviation for the binomial distribution.

MA 1125 Lecture 12 - Mean and Standard Deviation for the Binomial Distribution. Objectives: Mean and standard deviation for the binomial distribution. MA 5 Lecture - Mean and Standard Deviation for the Binomial Distribution Friday, September 9, 07 Objectives: Mean and standard deviation for the binomial distribution.. Mean and Standard Deviation of the

More information

MATH 118 Class Notes For Chapter 5 By: Maan Omran

MATH 118 Class Notes For Chapter 5 By: Maan Omran MATH 118 Class Notes For Chapter 5 By: Maan Omran Section 5.1 Central Tendency Mode: the number or numbers that occur most often. Median: the number at the midpoint of a ranked data. Ex1: The test scores

More information

4 Random Variables and Distributions

4 Random Variables and Distributions 4 Random Variables and Distributions Random variables A random variable assigns each outcome in a sample space. e.g. called a realization of that variable to Note: We ll usually denote a random variable

More information

A probability distribution shows the possible outcomes of an experiment and the probability of each of these outcomes.

A probability distribution shows the possible outcomes of an experiment and the probability of each of these outcomes. Introduction In the previous chapter we discussed the basic concepts of probability and described how the rules of addition and multiplication were used to compute probabilities. In this chapter we expand

More information

Expectation Exercises.

Expectation Exercises. Expectation Exercises. Pages Problems 0 2,4,5,7 (you don t need to use trees, if you don t want to but they might help!), 9,-5 373 5 (you ll need to head to this page: http://phet.colorado.edu/sims/plinkoprobability/plinko-probability_en.html)

More information

CH 5 Normal Probability Distributions Properties of the Normal Distribution

CH 5 Normal Probability Distributions Properties of the Normal Distribution Properties of the Normal Distribution Example A friend that is always late. Let X represent the amount of minutes that pass from the moment you are suppose to meet your friend until the moment your friend

More information

Week 7. Texas A& M University. Department of Mathematics Texas A& M University, College Station Section 3.2, 3.3 and 3.4

Week 7. Texas A& M University. Department of Mathematics Texas A& M University, College Station Section 3.2, 3.3 and 3.4 Week 7 Oğuz Gezmiş Texas A& M University Department of Mathematics Texas A& M University, College Station Section 3.2, 3.3 and 3.4 Oğuz Gezmiş (TAMU) Topics in Contemporary Mathematics II Week7 1 / 19

More information

TOPIC: PROBABILITY DISTRIBUTIONS

TOPIC: PROBABILITY DISTRIBUTIONS TOPIC: PROBABILITY DISTRIBUTIONS There are two types of random variables: A Discrete random variable can take on only specified, distinct values. A Continuous random variable can take on any value within

More information

Chapter 7. Random Variables

Chapter 7. Random Variables Chapter 7 Random Variables Making quantifiable meaning out of categorical data Toss three coins. What does the sample space consist of? HHH, HHT, HTH, HTT, TTT, TTH, THT, THH In statistics, we are most

More information

FINAL REVIEW W/ANSWERS

FINAL REVIEW W/ANSWERS FINAL REVIEW W/ANSWERS ( 03/15/08 - Sharon Coates) Concepts to review before answering the questions: A population consists of the entire group of people or objects of interest to an investigator, while

More information

Math 14 Lecture Notes Ch The Normal Approximation to the Binomial Distribution. P (X ) = nc X p X q n X =

Math 14 Lecture Notes Ch The Normal Approximation to the Binomial Distribution. P (X ) = nc X p X q n X = 6.4 The Normal Approximation to the Binomial Distribution Recall from section 6.4 that g A binomial experiment is a experiment that satisfies the following four requirements: 1. Each trial can have only

More information

Finding the Sum of Consecutive Terms of a Sequence

Finding the Sum of Consecutive Terms of a Sequence Mathematics 451 Finding the Sum of Consecutive Terms of a Sequence In a previous handout we saw that an arithmetic sequence starts with an initial term b, and then each term is obtained by adding a common

More information

The Binomial Probability Distribution

The Binomial Probability Distribution The Binomial Probability Distribution MATH 130, Elements of Statistics I J. Robert Buchanan Department of Mathematics Fall 2017 Objectives After this lesson we will be able to: determine whether a probability

More information

STUDY SET 2. Continuous Probability Distributions. ANSWER: Without continuity correction P(X>10) = P(Z>-0.66) =

STUDY SET 2. Continuous Probability Distributions. ANSWER: Without continuity correction P(X>10) = P(Z>-0.66) = STUDY SET 2 Continuous Probability Distributions 1. The normal distribution is used to approximate the binomial under certain conditions. What is the best way to approximate the binomial using the normal?

More information

Stat 333 Lab Assignment #2

Stat 333 Lab Assignment #2 1 Stat 333 Lab Assignment #2 1. A consumer organization estimates that over a 1-year period 17% of cars will need to be repaired once, 7% will need repairs twice, and 4% will require three or more repairs.

More information

Chapter 5: Discrete Probability Distributions

Chapter 5: Discrete Probability Distributions Chapter 5: Discrete Probability Distributions Section 5.1: Basics of Probability Distributions As a reminder, a variable or what will be called the random variable from now on, is represented by the letter

More information

5.9: The Binomial Theorem

5.9: The Binomial Theorem 5.9: The Binomial Theorem Pascal s Triangle 1. Show that zz = 1 + ii is a solution to the fourth degree polynomial equation zz 4 zz 3 + 3zz 2 4zz + 6 = 0. 2. Show that zz = 1 ii is a solution to the fourth

More information

AP Statistics Section 6.1 Day 1 Multiple Choice Practice. a) a random variable. b) a parameter. c) biased. d) a random sample. e) a statistic.

AP Statistics Section 6.1 Day 1 Multiple Choice Practice. a) a random variable. b) a parameter. c) biased. d) a random sample. e) a statistic. A Statistics Section 6.1 Day 1 ultiple Choice ractice Name: 1. A variable whose value is a numerical outcome of a random phenomenon is called a) a random variable. b) a parameter. c) biased. d) a random

More information

STA 6166 Fall 2007 Web-based Course. Notes 10: Probability Models

STA 6166 Fall 2007 Web-based Course. Notes 10: Probability Models STA 6166 Fall 2007 Web-based Course 1 Notes 10: Probability Models We first saw the normal model as a useful model for the distribution of some quantitative variables. We ve also seen that if we make a

More information

2. Modeling Uncertainty

2. Modeling Uncertainty 2. Modeling Uncertainty Models for Uncertainty (Random Variables): Big Picture We now move from viewing the data to thinking about models that describe the data. Since the real world is uncertain, our

More information

Part 10: The Binomial Distribution

Part 10: The Binomial Distribution Part 10: The Binomial Distribution The binomial distribution is an important example of a probability distribution for a discrete random variable. It has wide ranging applications. One readily available

More information

Chapter 6: Random Variables. Ch. 6-3: Binomial and Geometric Random Variables

Chapter 6: Random Variables. Ch. 6-3: Binomial and Geometric Random Variables Chapter : Random Variables Ch. -3: Binomial and Geometric Random Variables X 0 2 3 4 5 7 8 9 0 0 P(X) 3???????? 4 4 When the same chance process is repeated several times, we are often interested in whether

More information

Examples: Random Variables. Discrete and Continuous Random Variables. Probability Distributions

Examples: Random Variables. Discrete and Continuous Random Variables. Probability Distributions Random Variables Examples: Random variable a variable (typically represented by x) that takes a numerical value by chance. Number of boys in a randomly selected family with three children. Possible values:

More information

3.2 Binomial and Hypergeometric Probabilities

3.2 Binomial and Hypergeometric Probabilities 3.2 Binomial and Hypergeometric Probabilities Ulrich Hoensch Wednesday, January 23, 2013 Example An urn contains ten balls, exactly seven of which are red. Suppose five balls are drawn at random and with

More information

Things to Learn (Key words, Notation & Formulae)

Things to Learn (Key words, Notation & Formulae) Things to Learn (Key words, Notation & Formulae) Key words: Percentage This means per 100 or out of 100 Equivalent Equivalent fractions, decimals and percentages have the same value. Example words Rise,

More information

Chapter 8 Probability Models

Chapter 8 Probability Models Chapter 8 Probability Models We ve already used the calculator to find probabilities based on normal models. There are many more models which are useful. This chapter explores three such models. Many types

More information

Discrete Random Variables and Their Probability Distributions

Discrete Random Variables and Their Probability Distributions Chapter 5 Discrete Random Variables and Their Probability Distributions Mean and Standard Deviation of a Discrete Random Variable Computing the mean and standard deviation of a discrete random variable

More information

STAT 3090 Test 2 - Version B Fall Student s Printed Name: PLEASE READ DIRECTIONS!!!!

STAT 3090 Test 2 - Version B Fall Student s Printed Name: PLEASE READ DIRECTIONS!!!! STAT 3090 Test 2 - Fall 2015 Student s Printed Name: Instructor: XID: Section #: Read each question very carefully. You are permitted to use a calculator on all portions of this exam. You are NOT allowed

More information

Bin(20,.5) and N(10,5) distributions

Bin(20,.5) and N(10,5) distributions STAT 600 Design of Experiments for Research Workers Lab 5 { Due Thursday, November 18 Example Weight Loss In a dietary study, 14 of 0 subjects lost weight. If weight is assumed to uctuate up or down by

More information

Determine whether the given procedure results in a binomial distribution. If not, state the reason why.

Determine whether the given procedure results in a binomial distribution. If not, state the reason why. Math 5.3 Binomial Probability Distributions Name 1) Binomial Distrbution: Determine whether the given procedure results in a binomial distribution. If not, state the reason why. 2) Rolling a single die

More information

Name Period AP Statistics Unit 5 Review

Name Period AP Statistics Unit 5 Review Name Period AP Statistics Unit 5 Review Multiple Choice 1. Jay Olshansky from the University of Chicago was quoted in Chance News as arguing that for the average life expectancy to reach 100, 18% of people

More information

The Normal Probability Distribution

The Normal Probability Distribution 1 The Normal Probability Distribution Key Definitions Probability Density Function: An equation used to compute probabilities for continuous random variables where the output value is greater than zero

More information

MA : Introductory Probability

MA : Introductory Probability MA 320-001: Introductory Probability David Murrugarra Department of Mathematics, University of Kentucky http://www.math.uky.edu/~dmu228/ma320/ Spring 2017 David Murrugarra (University of Kentucky) MA 320:

More information

PROBABILITY AND STATISTICS CHAPTER 4 NOTES DISCRETE PROBABILITY DISTRIBUTIONS

PROBABILITY AND STATISTICS CHAPTER 4 NOTES DISCRETE PROBABILITY DISTRIBUTIONS PROBABILITY AND STATISTICS CHAPTER 4 NOTES DISCRETE PROBABILITY DISTRIBUTIONS I. INTRODUCTION TO RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS A. Random Variables 1. A random variable x represents a value

More information

Statistics. Marco Caserta IE University. Stats 1 / 56

Statistics. Marco Caserta IE University. Stats 1 / 56 Statistics Marco Caserta marco.caserta@ie.edu IE University Stats 1 / 56 1 Random variables 2 Binomial distribution 3 Poisson distribution 4 Hypergeometric Distribution 5 Jointly Distributed Discrete Random

More information

STAT 3090 Test 2 - Version B Fall Student s Printed Name: PLEASE READ DIRECTIONS!!!!

STAT 3090 Test 2 - Version B Fall Student s Printed Name: PLEASE READ DIRECTIONS!!!! Student s Printed Name: Instructor: XID: Section #: Read each question very carefully. You are permitted to use a calculator on all portions of this exam. You are NOT allowed to use any textbook, notes,

More information

The Vickrey-Clarke-Groves Mechanism

The Vickrey-Clarke-Groves Mechanism July 8, 2009 This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. Dealing with Externalities We saw that the Vickrey auction was no longer efficient when there

More information

II - Probability. Counting Techniques. three rules of counting. 1multiplication rules. 2permutations. 3combinations

II - Probability. Counting Techniques. three rules of counting. 1multiplication rules. 2permutations. 3combinations II - Probability Counting Techniques three rules of counting 1multiplication rules 2permutations 3combinations Section 2 - Probability (1) II - Probability Counting Techniques 1multiplication rules In

More information

chapter 13: Binomial Distribution Exercises (binomial)13.6, 13.12, 13.22, 13.43

chapter 13: Binomial Distribution Exercises (binomial)13.6, 13.12, 13.22, 13.43 chapter 13: Binomial Distribution ch13-links binom-tossing-4-coins binom-coin-example ch13 image Exercises (binomial)13.6, 13.12, 13.22, 13.43 CHAPTER 13: Binomial Distributions The Basic Practice of Statistics

More information

Binomial Random Variables. Binomial Random Variables

Binomial Random Variables. Binomial Random Variables Bernoulli Trials Definition A Bernoulli trial is a random experiment in which there are only two possible outcomes - success and failure. 1 Tossing a coin and considering heads as success and tails as

More information

Section Distributions of Random Variables

Section Distributions of Random Variables Section 8.1 - Distributions of Random Variables Definition: A random variable is a rule that assigns a number to each outcome of an experiment. Example 1: Suppose we toss a coin three times. Then we could

More information

6.4 approximating binomial distr with normal curve.notebook January 26, compute the mean/ expected value for the above distribution.

6.4 approximating binomial distr with normal curve.notebook January 26, compute the mean/ expected value for the above distribution. Discrete: Countable (no fractions or decimals) Continuous: Measurable: distance, time, volume Binomial Distribution n = number of trials r = number of successes p = probability of success q = probability

More information

binomial day 1.notebook December 10, 2013 Probability Quick Review of Probability Distributions!

binomial day 1.notebook December 10, 2013 Probability Quick Review of Probability Distributions! Probability Binomial Distributions Day 1 Quick Review of Probability Distributions! # boys born in 4 births, x 0 1 2 3 4 Probability, P(x) 0.0625 0.25 0.375 0.25 0.0625 TWO REQUIREMENTS FOR A PROBABILITY

More information

Binomial and multinomial distribution

Binomial and multinomial distribution 1-Binomial distribution Binomial and multinomial distribution The binomial probability refers to the probability that a binomial experiment results in exactly "x" successes. The probability of an event

More information

Chapter 17 Probability Models

Chapter 17 Probability Models Chapter 17 Probability Models Overview Key Concepts Know how to tell if a situation involves Bernoulli trials. Be able to choose whether to use a Geometric or a Binomial model for a random variable involving

More information

Review. What is the probability of throwing two 6s in a row with a fair die? a) b) c) d) 0.333

Review. What is the probability of throwing two 6s in a row with a fair die? a) b) c) d) 0.333 Review In most card games cards are dealt without replacement. What is the probability of being dealt an ace and then a 3? Choose the closest answer. a) 0.0045 b) 0.0059 c) 0.0060 d) 0.1553 Review What

More information

The Binomial and Geometric Distributions. Chapter 8

The Binomial and Geometric Distributions. Chapter 8 The Binomial and Geometric Distributions Chapter 8 8.1 The Binomial Distribution A binomial experiment is statistical experiment that has the following properties: The experiment consists of n repeated

More information

6.1 Discrete & Continuous Random Variables. Nov 4 6:53 PM. Objectives

6.1 Discrete & Continuous Random Variables. Nov 4 6:53 PM. Objectives 6.1 Discrete & Continuous Random Variables examples vocab Objectives Today we will... - Compute probabilities using the probability distribution of a discrete random variable. - Calculate and interpret

More information

Test 2 Version A STAT 3090 Fall 2016

Test 2 Version A STAT 3090 Fall 2016 Multiple Choice: (Questions 1-20) Answer the following questions on the scantron provided using a #2 pencil. Bubble the response that best answers the question. Each multiple choice correct response is

More information

Section Distributions of Random Variables

Section Distributions of Random Variables Section 8.1 - Distributions of Random Variables Definition: A random variable is a rule that assigns a number to each outcome of an experiment. Example 1: Suppose we toss a coin three times. Then we could

More information

5.2 Random Variables, Probability Histograms and Probability Distributions

5.2 Random Variables, Probability Histograms and Probability Distributions Chapter 5 5.2 Random Variables, Probability Histograms and Probability Distributions A random variable (r.v.) can be either continuous or discrete. It takes on the possible values of an experiment. It

More information

Chapter 8. Binomial and Geometric Distributions

Chapter 8. Binomial and Geometric Distributions Chapter 8 Binomial and Geometric Distributions Lesson 8-1, Part 1 Binomial Distribution What is a Binomial Distribution? Specific type of discrete probability distribution The outcomes belong to two categories

More information

Random Variables CHAPTER 6.3 BINOMIAL AND GEOMETRIC RANDOM VARIABLES

Random Variables CHAPTER 6.3 BINOMIAL AND GEOMETRIC RANDOM VARIABLES Random Variables CHAPTER 6.3 BINOMIAL AND GEOMETRIC RANDOM VARIABLES Essential Question How can I determine whether the conditions for using binomial random variables are met? Binomial Settings When the

More information

STA 220H1F LEC0201. Week 7: More Probability: Discrete Random Variables

STA 220H1F LEC0201. Week 7: More Probability: Discrete Random Variables STA 220H1F LEC0201 Week 7: More Probability: Discrete Random Variables Recall: A sample space for a random experiment is the set of all possible outcomes of the experiment. Random Variables A random variable

More information

Probability Review. The Practice of Statistics, 4 th edition For AP* STARNES, YATES, MOORE

Probability Review. The Practice of Statistics, 4 th edition For AP* STARNES, YATES, MOORE Probability Review The Practice of Statistics, 4 th edition For AP* STARNES, YATES, MOORE Probability Models In Section 5.1, we used simulation to imitate chance behavior. Fortunately, we don t have to

More information

STAT 201 Chapter 6. Distribution

STAT 201 Chapter 6. Distribution STAT 201 Chapter 6 Distribution 1 Random Variable We know variable Random Variable: a numerical measurement of the outcome of a random phenomena Capital letter refer to the random variable Lower case letters

More information

Stat511 Additional Materials

Stat511 Additional Materials Binomial Random Variable Stat511 Additional Materials The first discrete RV that we will discuss is the binomial random variable. The binomial random variable is a result of observing the outcomes from

More information

Binomial and Normal Distributions. Example: Determine whether the following experiments are binomial experiments. Explain.

Binomial and Normal Distributions. Example: Determine whether the following experiments are binomial experiments. Explain. Binomial and Normal Distributions Objective 1: Determining if an Experiment is a Binomial Experiment For an experiment to be considered a binomial experiment, four things must hold: 1. The experiment is

More information

Section 5 3 The Mean and Standard Deviation of a Binomial Distribution!

Section 5 3 The Mean and Standard Deviation of a Binomial Distribution! Section 5 3 The Mean and Standard Deviation of a Binomial Distribution! Previous sections required that you to find the Mean and Standard Deviation of a Binomial Distribution by using the values from a

More information

Binomial Distribution. Normal Approximation to the Binomial

Binomial Distribution. Normal Approximation to the Binomial Binomial Distribution Normal Approximation to the Binomial /29 Homework Read Sec 6-6. Discussion Question pg 337 Do Ex 6-6 -4 2 /29 Objectives Objective: Use the normal approximation to calculate 3 /29

More information

When the observations of a quantitative random variable can take on only a finite number of values, or a countable number of values.

When the observations of a quantitative random variable can take on only a finite number of values, or a countable number of values. 5.1 Introduction to Random Variables and Probability Distributions Statistical Experiment - any process by which an observation (or measurement) is obtained. Examples: 1) Counting the number of eggs in

More information

Decision Trees: Booths

Decision Trees: Booths DECISION ANALYSIS Decision Trees: Booths Terri Donovan recorded: January, 2010 Hi. Tony has given you a challenge of setting up a spreadsheet, so you can really understand whether it s wiser to play in

More information

Chapter 7. Sampling Distributions and the Central Limit Theorem

Chapter 7. Sampling Distributions and the Central Limit Theorem Chapter 7. Sampling Distributions and the Central Limit Theorem 1 Introduction 2 Sampling Distributions related to the normal distribution 3 The central limit theorem 4 The normal approximation to binomial

More information

Statistics Chapter 8

Statistics Chapter 8 Statistics Chapter 8 Binomial & Geometric Distributions Time: 1.5 + weeks Activity: A Gaggle of Girls The Ferrells have 3 children: Jennifer, Jessica, and Jaclyn. If we assume that a couple is equally

More information