Math 14 Lecture Notes Ch. 4.3

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.

Part 1 In which we meet the law of averages. The Law of Averages. The Expected Value & The Standard Error. Where Are We Going?

1 The Law of Averages The Expected Value & The Standard Error Where Are We Going? Sums of random numbers The law of averages Box models for generating random numbers Sums of draws: the Expected Value Standard

Lesson 97 - Binomial Distributions IBHL2 - SANTOWSKI

Lesson 97 - Binomial Distributions IBHL2 - SANTOWSKI Opening Exercise: Example #: (a) Use a tree diagram to answer the following: You throwing a bent coin 3 times where P(H) = / (b) THUS, find the probability

Opening Exercise: Lesson 91 - Binomial Distributions IBHL2 - SANTOWSKI

08-0- Lesson 9 - Binomial Distributions IBHL - SANTOWSKI Opening Exercise: Example #: (a) Use a tree diagram to answer the following: You throwing a bent coin times where P(H) = / (b) THUS, find the probability

Binomial Distributions

Binomial Distributions Binomial Experiment The experiment is repeated for a fixed number of trials, where each trial is independent of the other trials There are only two possible outcomes of interest

Chapter 4 Discrete Random variables

Chapter 4 Discrete Random variables A is a variable that assumes numerical values associated with the random outcomes of an experiment, where only one numerical value is assigned to each sample point.

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

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.

Shifting our focus. We were studying statistics (data, displays, sampling...) The next few lectures focus on probability (randomness) Why?

Probability Introduction Shifting our focus We were studying statistics (data, displays, sampling...) The next few lectures focus on probability (randomness) Why? What is Probability? Probability is used

MATH 264 Problem Homework I

MATH Problem Homework I Due to December 9, 00@:0 PROBLEMS & SOLUTIONS. A student answers a multiple-choice examination question that offers four possible answers. Suppose that the probability that the

Chapter 4 Discrete Random variables

Chapter 4 Discrete Random variables A is a variable that assumes numerical values associated with the random outcomes of an experiment, where only one numerical value is assigned to each sample point.

Chapter 3. Discrete Probability Distributions

Chapter 3 Discrete Probability Distributions 1 Chapter 3 Overview Introduction 3-1 The Binomial Distribution 3-2 Other Types of Distributions 2 Chapter 3 Objectives Find the exact probability for X successes

Chapter 5. Discrete Probability Distributions. McGraw-Hill, Bluman, 7 th ed, Chapter 5 1

Chapter 5 Discrete Probability Distributions McGraw-Hill, Bluman, 7 th ed, Chapter 5 1 Chapter 5 Overview Introduction 5-1 Probability Distributions 5-2 Mean, Variance, Standard Deviation, and Expectation

Lecture 9. Probability Distributions. Outline. Outline

Outline Lecture 9 Probability Distributions 6-1 Introduction 6- Probability Distributions 6-3 Mean, Variance, and Expectation 6-4 The Binomial Distribution Outline 7- Properties of the Normal 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

Lecture 9. Probability Distributions

Lecture 9 Probability Distributions Outline 6-1 Introduction 6-2 Probability Distributions 6-3 Mean, Variance, and Expectation 6-4 The Binomial Distribution Outline 7-2 Properties of the Normal Distribution

Chapter 3 - Lecture 5 The Binomial Probability Distribution

Chapter 3 - Lecture 5 The Binomial Probability October 12th, 2009 Experiment Examples Moments and moment generating function of a Binomial Random Variable Outline Experiment Examples A binomial experiment

Simple Random Sample

Simple Random Sample A simple random sample (SRS) of size n consists of n elements from the population chosen in such a way that every set of n elements has an equal chance to be the sample actually selected.

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

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

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

Fall 2015 Math 141:505 Exam 3 Form A

Fall 205 Math 4:505 Exam 3 Form A Last Name: First Name: Exam Seat #: UIN: On my honor, as an Aggie, I have neither given nor received unauthorized aid on this academic work Signature: INSTRUCTIONS Part

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

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:

PROBABILITY DISTRIBUTIONS

CHAPTER 3 PROBABILITY DISTRIBUTIONS Page Contents 3.1 Introduction to Probability Distributions 51 3.2 The Normal Distribution 56 3.3 The Binomial Distribution 60 3.4 The Poisson Distribution 64 Exercise

Problem A Grade x P(x) To get "C" 1 or 2 must be 1 0.05469 B A 2 0.16410 3 0.27340 4 0.27340 5 0.16410 6 0.05470 7 0.00780 0.2188 0.5468 0.2266 Problem B Grade x P(x) To get "C" 1 or 2 must 1 0.31150 be

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

Binomial Distributions

Binomial Distributions A binomial experiment is a probability experiment that satisfies these conditions. 1. The experiment has a fixed number of trials, where each trial is independent of the other trials.

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

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

***SECTION 8.1*** The Binomial Distributions

***SECTION 8.1*** The Binomial Distributions CHAPTER 8 ~ The Binomial and Geometric Distributions In practice, we frequently encounter random phenomenon where there are two outcomes of interest. For example,

8.4: The Binomial Distribution

c Dr Oksana Shatalov, Spring 2012 1 8.4: The Binomial Distribution Binomial Experiments have the following properties: 1. The number of trials in the experiment is fixed. 2. There are 2 possible outcomes

The Binomial distribution

The Binomial distribution Examples and Definition Binomial Model (an experiment ) 1 A series of n independent trials is conducted. 2 Each trial results in a binary outcome (one is labeled success the other

Example 1: Identify the following random variables as discrete or continuous: a) Weight of a package. b) Number of students in a first-grade classroom

Section 5-1 Probability Distributions I. Random Variables A variable x is a if the value that it assumes, corresponding to the of an experiment, is a or event. A random variable is if it potentially can

Chapter. Section 4.2. Chapter 4. Larson/Farber 5 th ed 1. Chapter Outline. Discrete Probability Distributions. Section 4.

Chapter Discrete Probability s Chapter Outline 1 Probability s 2 Binomial s 3 More Discrete Probability s Copyright 2015, 2012, and 2009 Pearson Education, Inc 1 Copyright 2015, 2012, and 2009 Pearson

Binomial formulas: The binomial coefficient is the number of ways of arranging k successes among n observations.

Chapter 8 Notes Binomial and Geometric Distribution Often times we are interested in an event that has only two outcomes. For example, we may wish to know the outcome of a free throw shot (good or missed),

Section 8.4 The Binomial Distribution

Section 8.4 The Binomial Distribution Binomial Experiment A binomial experiment has the following properties: 1. The number of trials in the experiment is fixed. 2. There are two outcomes of each trial:

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

Math Week in Review #10. Experiments with two outcomes ( success and failure ) are called Bernoulli or binomial trials.

Math 141 Spring 2006 c Heather Ramsey Page 1 Section 8.4 - Binomial Distribution Math 141 - Week in Review #10 Experiments with two outcomes ( success and failure ) are called Bernoulli or binomial trials.

Let X be the number that comes up on the next roll of the die.

Chapter 6 - Discrete Probability Distributions 6.1 Random Variables Introduction If we roll a fair die, the possible outcomes are the numbers 1, 2, 3, 4, 5, and 6, and each of these numbers has probability

Math 361. Day 8 Binomial Random Variables pages 27 and 28 Inv Do you have ESP? Inv. 1.3 Tim or Bob?

Math 361 Day 8 Binomial Random Variables pages 27 and 28 Inv. 1.2 - Do you have ESP? Inv. 1.3 Tim or Bob? Inv. 1.1: Friend or Foe Review Is a particular study result consistent with the null model? Learning

4.1 Probability Distributions

Probability and Statistics Mrs. Leahy Chapter 4: Discrete Probability Distribution ALWAYS KEEP IN MIND: The Probability of an event is ALWAYS between: and!!!! 4.1 Probability Distributions Random Variables

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

Lecture 6 Probability

Faculty of Medicine Epidemiology and Biostatistics الوبائيات واإلحصاء الحيوي (31505204) Lecture 6 Probability By Hatim Jaber MD MPH JBCM PhD 3+4-7-2018 1 Presentation outline 3+4-7-2018 Time Introduction-

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:

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

What is the probability of success? Failure? How could we do this simulation using a random number table?

Probability Ch.4, sections 4.2 & 4.3 Binomial and Geometric Distributions Name: Date: Pd: 4.2. What is a binomial distribution? How do we find the probability of success? Suppose you have three daughters.

Section Random Variables

Section 6.2 - Random Variables According to the Bureau of the Census, the latest family data pertaining to family size for a small midwestern town, Nomore, is shown in Table 6.. If a family from this town

MATH 112 Section 7.3: Understanding Chance

MATH 112 Section 7.3: Understanding Chance Prof. Jonathan Duncan Walla Walla University Autumn Quarter, 2007 Outline 1 Introduction to Probability 2 Theoretical vs. Experimental Probability 3 Advanced

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"

A random variable (r. v.) is a variable whose value is a numerical outcome of a random phenomenon.

Chapter 14: random variables p394 A random variable (r. v.) is a variable whose value is a numerical outcome of a random phenomenon. Consider the experiment of tossing a coin. Define a random variable

A random variable is a (typically represented by ) that has a. value, determined by, A probability distribution is a that gives the

5.2 RANDOM VARIABLES A random variable is a (typically represented by ) that has a value, determined by, for each of a. A probability distribution is a that gives the for each value of the. It is often

Chapter 11. Data Descriptions and Probability Distributions. Section 4 Bernoulli Trials and Binomial Distribution

Chapter 11 Data Descriptions and Probability Distributions Section 4 Bernoulli Trials and Binomial Distribution 1 Learning Objectives for Section 11.4 Bernoulli Trials and Binomial Distributions The student

7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4

7. For the table that follows, answer the following questions: x y 1-1/4 2-1/2 3-3/4 4 - Would the correlation between x and y in the table above be positive or negative? The correlation is negative. -

Answer Key: Quiz2-Chapter5: Discrete Probability Distribution

Economics 70: Applied Business Statistics For Economics & Business (Summer 01) Answer Key: Quiz-Chapter5: Discrete Probability Distribution The number of electrical outages in a city varies from day to

Stats SB Notes 4.2 Completed.notebook February 22, Feb 21 11:39 AM. Chapter Outline

Stats SB Notes 42 Completednotebook February 22, 2017 Chapter 4 Discrete Probability Distributions Chapter Outline 41 Probability Distributions 42 Binomial Distributions 43 More Discrete Probability Distributions

Math 1070 Sample Exam 2 Spring 2015

University of Connecticut Department of Mathematics Math 1070 Sample Exam 2 Spring 2015 Name: Instructor Name: Section: Exam 2 will cover Sections 4.6-4.7, 5.3-5.4, 6.1-6.4, and F.1-F.4. This sample exam

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

The binomial distribution p314

The binomial distribution p314 Example: A biased coin (P(H) = p = 0.6) ) is tossed 5 times. Let X be the number of H s. Fine P(X = 2). This X is a binomial r. v. The binomial setting p314 1. There are

Chapter 5 Probability Distributions. Section 5-2 Random Variables. Random Variable Probability Distribution. Discrete and Continuous Random Variables

Chapter 5 Probability Distributions Section 5-2 Random Variables 5-2 Random Variables 5-3 Binomial Probability Distributions 5-4 Mean, Variance and Standard Deviation for the Binomial Distribution Random

Chapter 4 and 5 Note Guide: Probability Distributions

Chapter 4 and 5 Note Guide: Probability Distributions Probability Distributions for a Discrete Random Variable A discrete probability distribution function has two characteristics: Each probability is

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

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

Section 6.3 Binomial and Geometric Random Variables

Section 6.3 Binomial and Geometric Random Variables Mrs. Daniel AP Stats Binomial Settings A binomial setting arises when we perform several independent trials of the same chance process and record the

Probability Distributions

4.1 Probability Distributions Random Variables A random variable x represents a numerical value associated with each outcome of a probability distribution. A random variable is discrete if it has a finite

Chapter 3 - Lecture 3 Expected Values of Discrete Random Va

Chapter 3 - Lecture 3 Expected Values of Discrete Random Variables October 5th, 2009 Properties of expected value Standard deviation Shortcut formula Properties of the variance Properties of expected value

Binomal and Geometric Distributions

Binomal and Geometric Distributions Sections 3.2 & 3.3 Cathy Poliak, Ph.D. cathy@math.uh.edu Office in Fleming 11c Department of Mathematics University of Houston Lecture 7-2311 Cathy Poliak, Ph.D. cathy@math.uh.edu

Study Guide: Chapter 5, Sections 1 thru 3 (Probability Distributions)

Study Guide: Chapter 5, Sections 1 thru 3 (Probability Distributions) Name SHORT ANSWER. 1) Fill in the missing value so that the following table represents a probability distribution. x 1 2 3 4 P(x) 0.09

The normal distribution is a theoretical model derived mathematically and not empirically.

Sociology 541 The Normal Distribution Probability and An Introduction to Inferential Statistics Normal Approximation The normal distribution is a theoretical model derived mathematically and not empirically.

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

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

12 Math Chapter Review April 16 th, Multiple Choice Identify the choice that best completes the statement or answers the question.

Multiple Choice Identify the choice that best completes the statement or answers the question. 1. Which situation does not describe a discrete random variable? A The number of cell phones per household.

5.1 Personal Probability

5. Probability Value Page 1 5.1 Personal Probability Although we think probability is something that is confined to math class, in the form of personal probability it is something we use to make decisions

Probability and Statistics

Probability and Statistics Alvin Lin Probability and Statistics: January 2017 - May 2017 Binomial Random Variables There are two balls marked S and F in a basket. Select a ball 3 times with replacement.

Chapter 8: The Binomial and Geometric Distributions

Chapter 8: The Binomial and Geometric Distributions 8.1 Binomial Distributions 8.2 Geometric Distributions 1 Let me begin with an example My best friends from Kent School had three daughters. What is the

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

Math 14 Lecture Notes Ch Mean

4. Mean, Expected Value, and Standard Deviation Mean Recall the formula from section. for find the population mean of a data set of elements µ = x 1 + x + x +!+ x = x i i=1 We can find the mean of the

Binomial and Geometric Distributions

Binomial and Geometric Distributions Section 3.2 & 3.3 Cathy Poliak, Ph.D. cathy@math.uh.edu Office hours: T Th 2:30 pm - 5:15 pm 620 PGH Department of Mathematics University of Houston February 11, 2016

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

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

L04: Homework Answer Key

L04: Homework Answer Key Instructions: You are encouraged to collaborate with other students on the homework, but it is important that you do your own work. Before working with someone else on the assignment,

Instructor: A.E.Cary. Math 243 Exam 2

Name: Instructor: A.E.Cary Instructions: Show all your work in a manner consistent with that demonstrated in class. Round your answers where appropriate. Use 3 decimal places when rounding answers. In

Assignment 3 - Statistics. n n! (n r)!r! n = 1,2,3,...

Assignment 3 - Statistics Name: Permutation: Combination: n n! P r = (n r)! n n! C r = (n r)!r! n = 1,2,3,... n = 1,2,3,... The Fundamental Counting Principle: If two indepndent events A and B can happen

List of Online Quizzes: Quiz7: Basic Probability Quiz 8: Expectation and sigma. Quiz 9: Binomial Introduction Quiz 10: Binomial Probability

List of Online Homework: Homework 6: Random Variables and Discrete Variables Homework7: Expected Value and Standard Dev of a Variable Homework8: The Binomial Distribution List of Online Quizzes: Quiz7:

Section 8.4 The Binomial Distribution. (a) Rolling a fair die 20 times and observing how many heads appear. s

Section 8.4 The Binomial Distribution Binomial Experiment A binomial experiment has the following properties: 1. The number of trials in the experiment is fixed. 2. There are two outcomes of each trial:

Chapter 4. Section 4.1 Objectives. Random Variables. Random Variables. Chapter 4: Probability Distributions

Chapter 4: Probability s 4. Probability s 4. Binomial s Section 4. Objectives Distinguish between discrete random variables and continuous random variables Construct a discrete probability distribution

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

Probability Distributions. Definitions Discrete vs. Continuous Mean and Standard Deviation TI 83/84 Calculator Binomial Distribution

Probability Distributions Definitions Discrete vs. Continuous Mean and Standard Deviation TI 83/84 Calculator Binomial Distribution Definitions Random Variable: a variable that has a single numerical value

Binomial Random Variable - The count X of successes in a binomial setting

6.3.1 Binomial Settings and Binomial Random Variables What do the following scenarios have in common? Toss a coin 5 times. Count the number of heads. Spin a roulette wheel 8 times. Record how many times

Unit 4 Bernoulli and Binomial Distributions Week #6 - Practice Problems. SOLUTIONS Revised (enhanced for q4)

PubHlth 540 Introductory Biostatistics Page 1 of 6 Unit 4 Bernoulli and Binomial Distributions Week #6 - Practice Problems SOLUTIONS Revised (enhanced for q4) 10-29-2008 1. This exercise gives you practice

Example - Let X be the number of boys in a 4 child family. Find the probability distribution table:

Chapter8 Probability Distributions and Statistics Section 8.1 Distributions of Random Variables tthe value of the result of the probability experiment is a RANDOM VARIABLE. Example - Let X be the number

Statistics 6 th Edition

Statistics 6 th Edition Chapter 5 Discrete Probability Distributions Chap 5-1 Definitions Random Variables Random Variables Discrete Random Variable Continuous Random Variable Ch. 5 Ch. 6 Chap 5-2 Discrete

Applied Mathematics 12 Extra Practice Exercises Chapter 3

H E LP Applied Mathematics Extra Practice Exercises Chapter Tutorial., page 98. A bag contains 5 red balls, blue balls, and green balls. For each of the experiments described below, complete the given

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

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

Probability & Statistics Chapter 5: Binomial Distribution

Probability & Statistics Chapter 5: Binomial Distribution Notes and Examples Binomial Distribution When a variable can be viewed as having only two outcomes, call them success and failure, it may be considered

Unit 04 Review. Probability Rules

Unit 04 Review Probability Rules A sample space contains all the possible outcomes observed in a trial of an experiment, a survey, or some random phenomenon. The sum of the probabilities for all possible

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

MA 1125 Lecture 18 - Normal Approximations to Binomial Distributions. Objectives: Compute probabilities for a binomial as a normal distribution.

MA 25 Lecture 8 - Normal Approximations to Binomial Distributions Friday, October 3, 207 Objectives: Compute probabilities for a binomial as a normal distribution.. Normal Approximations to the Binomial

Chapter 2: Probability

Slide 2.1 Chapter 2: Probability Probability underlies statistical inference - the drawing of conclusions from a sample of data. If samples are drawn at random, their characteristics (such as the sample