6.4 approximating binomial distr with normal curve.notebook January 26, compute the mean/ expected value for the above distribution.
|
|
- Donald Newman
- 5 years ago
- Views:
Transcription
1 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 of failure q = 1 p Make a histogram for the binomial distribution where p =.25, q =.75 and n = 3. Find the P(r) values in the chart: or Type 0 3 into list 1 and binomialpdf(3,.25,l1) into list 2 r P(r) compute the mean/ expected value for the above distribution. 1. Can put r values into list 1 and probabilities into list 2. 1 var stat L1, L2 2. Can multiply 0(.422) + 1(.422) + 2(.141) + 3(.016) 3. Can use the formula answer:.751 answer:.752 answer:.75 compute the standard deviation for the distributions answer:.7 answer:.7
2 Watch what happens to the shape of the histogram as we increase the value of n. np =.75 nq=2.25 np = 2.5 nq= 7.5
3 np = 6.25 nq= np = 12.5 nq= 37.5
4 If np > 5 and nq > 5 then a binomial distribution can be approximated by a normal distribution. (Use the techniques you learned in chapter 6) Use the continuity correction to get a better approximation. If you are finding the area to the right If you are finding the area to the right, then subtract.5 from r. P(r > 8) will become P( x > 7.5)
5 If you are finding the area to the left If you are finding the area to the left, then add on.5 to r. so P(r < 8) will become P(x < 8.5)
6 If you are finding the area between two values If you are finding the area between two values then do both: so P(4 < r < 7) will become P(3.5 < x < 7.5)
7 Compare the two methods: If we know that p =.25 and n = 25 then find P(r > 8). Binomial n = 25 p = 0.25 P(r 8) reminders put 0 25 in L1 hover over L2 type binomialpdf (n,p,l1) answer P(r > 8 ) = = 27.25%
8 If we know that p =.25 and n = 25 then find the P(r > 8). Use the Normal/Standard Normal curve: Need reminders and changes to for better accuracy answer
9 About 40% of all US adults will try to pad their insurance claims. Suppose that you are the director of an insurance adjustment office. Your office has just received 128 insurance claims to be processed in the next few days. What is the probability that half or more of the claims have been padded? discrete or continuous? n = 128 p =.4 q = 1.4=.6 Check: n p= n q= Continuity Correction: r > 64 x > 63.5
10 About 40% of all US adults will try to pad their insurance claims. Suppose that you are the director of an insurance adjustment office. Your office has just received 128 insurance claims to be processed in the next few days. What is the probability that fewer than 45 of the claims have been padded? discrete or continuous? n = 128 p =.4 q = 1.4=.6 Check: n p= n q= Continuity Correction: r < 45 x < 45.5
11 About 40% of all US adults will try to pad their insurance claims. Suppose that you are the director of an insurance adjustment office. Your office has just received 128 insurance claims to be processed in the next few days. What is the probability that from 40 to 60 of the claims have been padded? discrete or continuous? n = 128 p =.4 q = 1.4=.6 Check: n p= n q= Continuity Correction: 40 < r < 60
12 6.4 approximating binomial distr with normal curve.notebook January 26, 2018
13 USA Today reported that 11% of all books sold are romance oriented. If a local bookstore sells 316 books on a given day, what is the probability that a) no more than 40 are romances? discrete or continuous? n = 316 p =.11 q = 1.11=.89 Check: n p= n q= Continuity Correction: r < 40 x < 40.5
14 USA Today reported that 11% of all books sold are romance oriented. If a local bookstore sells 316 books on a given day, what is the probability that a) at least 25 are romances? discrete or continuous? n = 316 p =.11 q = 1.11=.89 Check: n p= n q= Continuity Correction: r > 25 x > 24.5
15 6.4 approximating binomial distr with normal curve.notebook January 26, 2018
16 USA Today reported that 11% of all books sold are romance oriented. If a local bookstore sells 316 books on a given day, what is the probability that c) between 25 and 40 are romances? discrete or continuous? n = 316 p =.11 q = 1.11=.89 Check: n p= n q= Continuity Correction: 25 < r < < x < 40.5
17 d) in the solution to this problem what was n? p? q? Does it appear that both np and nq are larger than 5? Why is this important consideration?
18
19
20 P. 341 #3 15 choose any 9 note: s d n
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 informationMath 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 informationThe 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 informationUsing the Central Limit Theorem It is important for you to understand when to use the CLT. If you are being asked to find the probability of the
Using the Central Limit Theorem It is important for you to understand when to use the CLT. If you are being asked to find the probability of the mean, use the CLT for the mean. If you are being asked to
More informationExamples: 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 information1 / * / * / * / * / * 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 informationMath Tech IIII, Mar 13
Math Tech IIII, Mar 13 The Binomial Distribution III Book Sections: 4.2 Essential Questions: What do I need to know about the binomial distribution? Standards: DA-5.6 What Makes a Binomial Experiment?
More informationChapter 6 Confidence Intervals Section 6-1 Confidence Intervals for the Mean (Large Samples) Estimating Population Parameters
Chapter 6 Confidence Intervals Section 6-1 Confidence Intervals for the Mean (Large Samples) Estimating Population Parameters VOCABULARY: Point Estimate a value for a parameter. The most point estimate
More informationMAKING SENSE OF DATA Essentials series
MAKING SENSE OF DATA Essentials series THE NORMAL DISTRIBUTION Copyright by City of Bradford MDC Prerequisites Descriptive statistics Charts and graphs The normal distribution Surveys and sampling Correlation
More informationStatistics (This summary is for chapters 18, 29 and section H of chapter 19)
Statistics (This summary is for chapters 18, 29 and section H of chapter 19) Mean, Median, Mode Mode: most common value Median: middle value (when the values are in order) Mean = total how many = x n =
More informationSection 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 informationChapter 6 Confidence Intervals
Chapter 6 Confidence Intervals Section 6-1 Confidence Intervals for the Mean (Large Samples) VOCABULARY: Point Estimate A value for a parameter. The most point estimate of the population parameter is the
More informationGraphing a Binomial Probability Distribution Histogram
Chapter 6 8A: Using a Normal Distribution to Approximate a Binomial Probability Distribution Graphing a Binomial Probability Distribution Histogram Lower and Upper Class Boundaries are used to graph the
More informationBinomial 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 informationProbability 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
More informationStatistics (This summary is for chapters 17, 28, 29 and section G of chapter 19)
Statistics (This summary is for chapters 17, 28, 29 and section G of chapter 19) Mean, Median, Mode Mode: most common value Median: middle value (when the values are in order) Mean = total how many = x
More informationOverview. Definitions. Definitions. Graphs. Chapter 5 Probability Distributions. probability distributions
Chapter 5 Probability Distributions 5-1 Overview 5-2 Random Variables 5-3 Binomial Probability Distributions 5-4 Mean, Variance, and Standard Deviation for the Binomial Distribution 5-5 The Poisson Distribution
More informationAP Statistics Ch 8 The Binomial and Geometric Distributions
Ch 8.1 The Binomial Distributions The Binomial Setting A situation where these four conditions are satisfied is called a binomial setting. 1. Each observation falls into one of just two categories, which
More informationChapter 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
More informationMidterm Test 1 (Sample) Student Name (PRINT):... Student Signature:... Use pencil, so that you can erase and rewrite if necessary.
MA 180/418 Midterm Test 1 (Sample) Student Name (PRINT):............................................. Student Signature:................................................... Use pencil, so that you can erase
More informationThe Normal Approximation to the Binomial Distribution
7 6 The Normal Approximation to the Binomial Distribution Objective 7. Use the normal approximation to compute probabilities for a binomial variable. The normal distribution is often used to solve problems
More informationSection Introduction to Normal Distributions
Section 6.1-6.2 Introduction to Normal Distributions 2012 Pearson Education, Inc. All rights reserved. 1 of 105 Section 6.1-6.2 Objectives Interpret graphs of normal probability distributions Find areas
More informationMath Tech IIII, Mar 6
Math Tech IIII, Mar 6 The Binomial Distribution II Book Sections: 4.2 Essential Questions: How can I compute the probability of any event? What do I need to know about the binomial distribution? Standards:
More informationLecture 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 informationSection 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 informationMA 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
More informationNo, because np = 100(0.02) = 2. The value of np must be greater than or equal to 5 to use the normal approximation.
1) If n 100 and p 0.02 in a binomial experiment, does this satisfy the rule for a normal approximation? Why or why not? No, because np 100(0.02) 2. The value of np must be greater than or equal to 5 to
More information5.4 Normal Approximation of the Binomial Distribution Lesson MDM4U Jensen
5.4 Normal Approximation of the Binomial Distribution Lesson MDM4U Jensen Review From Yesterday Bernoulli Trials have 3 properties: 1. 2. 3. Binomial Probability Distribution In a binomial experiment with
More informationChapter 4 Probability Distributions
Slide 1 Chapter 4 Probability Distributions Slide 2 4-1 Overview 4-2 Random Variables 4-3 Binomial Probability Distributions 4-4 Mean, Variance, and Standard Deviation for the Binomial Distribution 4-5
More information5.4 Normal Approximation of the Binomial Distribution
5.4 Normal Approximation of the Binomial Distribution Bernoulli Trials have 3 properties: 1. Only two outcomes - PASS or FAIL 2. n identical trials Review from yesterday. 3. Trials are independent - probability
More information5.2 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 informationThe 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 informationHonors Statistics. Daily Agenda
Honors Statistics Aug 23-8:26 PM Daily Agenda 3. Review 6.3 Notes Quiz Aug 23-8:31 PM 1 Jan 27-2:30 PM Dec 10-9:59 AM 2 May 15-6:15 PM in a randomly selected group of three? = = ( May 15-6:17 PM 3 5. Draw
More informationThe 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 informationProbability is the tool used for anticipating what the distribution of data should look like under a given model.
AP Statistics NAME: Exam Review: Strand 3: Anticipating Patterns Date: Block: III. Anticipating Patterns: Exploring random phenomena using probability and simulation (20%-30%) Probability is the tool used
More informationThe Central Limit Theorem
Section 6-5 The Central Limit Theorem I. Sampling Distribution of Sample Mean ( ) Eample 1: Population Distribution Table 2 4 6 8 P() 1/4 1/4 1/4 1/4 μ (a) Find the population mean and population standard
More informationChapter 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 informationchapter 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 informationChapter 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 informationCH 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 informationChapter 4. The Normal Distribution
Chapter 4 The Normal Distribution 1 Chapter 4 Overview Introduction 4-1 Normal Distributions 4-2 Applications of the Normal Distribution 4-3 The Central Limit Theorem 4-4 The Normal Approximation to the
More information30 Wyner Statistics Fall 2013
30 Wyner Statistics Fall 2013 CHAPTER FIVE: DISCRETE PROBABILITY DISTRIBUTIONS Summary, Terms, and Objectives A probability distribution shows the likelihood of each possible outcome. This chapter deals
More informationAMS7: WEEK 4. CLASS 3
AMS7: WEEK 4. CLASS 3 Sampling distributions and estimators. Central Limit Theorem Normal Approximation to the Binomial Distribution Friday April 24th, 2015 Sampling distributions and estimators REMEMBER:
More information11.5: Normal Distributions
11.5: Normal Distributions 11.5.1 Up to now, we ve dealt with discrete random variables, variables that take on only a finite (or countably infinite we didn t do these) number of values. A continuous random
More informationChapter Five. The Binomial Distribution and Related Topics
Chapter Five The Binomial Distribution and Related Topics Section 2 Binomial Probabilities Essential Question What are the three methods for solving binomial probability questions? Explain each of the
More informationBinomial Probabilities The actual probability that P ( X k ) the formula n P X k p p. = for any k in the range {0, 1, 2,, n} is given by. n n!
Introduction We are often more interested in experiments in which there are two outcomes of interest (success/failure, make/miss, yes/no, etc.). In this chapter we study two types of probability distributions
More informationOverview. Definitions. Definitions. Graphs. Chapter 4 Probability Distributions. probability distributions
Chapter 4 Probability Distributions 4-1 Overview 4-2 Random Variables 4-3 Binomial Probability Distributions 4-4 Mean, Variance, and Standard Deviation for the Binomial Distribution 4-5 The Poisson Distribution
More information7 THE CENTRAL LIMIT THEOREM
CHAPTER 7 THE CENTRAL LIMIT THEOREM 373 7 THE CENTRAL LIMIT THEOREM Figure 7.1 If you want to figure out the distribution of the change people carry in their pockets, using the central limit theorem and
More informationChapter 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* Source:
Problem: A recent report from Gallup stated that most teachers don t want to be armed in school. Gallup asked K-12 teachers if they would be willing to be trained so they could carry a gun at school. Eighteen
More informationMATH 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 informationMath 227 Elementary Statistics. Bluman 5 th edition
Math 227 Elementary Statistics Bluman 5 th edition CHAPTER 6 The Normal Distribution 2 Objectives Identify distributions as symmetrical or skewed. Identify the properties of the normal distribution. Find
More informationLecture Slides. Elementary Statistics Tenth Edition. by Mario F. Triola. and the Triola Statistics Series
Lecture Slides Elementary Statistics Tenth Edition and the Triola Statistics Series by Mario F. Triola Slide 1 Chapter 5 Probability Distributions 5-1 Overview 5-2 Random Variables 5-3 Binomial Probability
More informationMidTerm 1) Find the following (round off to one decimal place):
MidTerm 1) 68 49 21 55 57 61 70 42 59 50 66 99 Find the following (round off to one decimal place): Mean = 58:083, round off to 58.1 Median = 58 Range = max min = 99 21 = 78 St. Deviation = s = 8:535,
More informationNotes 12.8: Normal Distribution
Notes 12.8: Normal Distribution For many populations, the distribution of events are relatively close to the average or mean. The further you go out both above and below the mean, there are fewer number
More informationSampling & populations
Sampling & populations Sample proportions Sampling distribution - small populations Sampling distribution - large populations Sampling distribution - normal distribution approximation Mean & variance of
More informationConfidence Intervals for the Mean. When σ is known
Confidence Intervals for the Mean When σ is known Objective Find the confidence interval for the mean when s is known. Intro Suppose a college president wishes to estimate the average age of students attending
More informationChapter 5 Normal Probability Distributions
Chapter 5 Normal Probability Distributions Section 5-1 Introduction to Normal Distributions and the Standard Normal Distribution A The normal distribution is the most important of the continuous probability
More informationMath 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 informationProbability Distribution Unit Review
Probability Distribution Unit Review Topics: Pascal's Triangle and Binomial Theorem Probability Distributions and Histograms Expected Values, Fair Games of chance Binomial Distributions Hypergeometric
More informationChapter 8: Binomial and Geometric Distributions
Chapter 8: Binomial and Geometric Distributions Section 8.1 Binomial Distributions The Practice of Statistics, 4 th edition For AP* STARNES, YATES, MOORE Section 8.1 Binomial Distribution Learning Objectives
More informationChapter 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
More informationPROBABILITY 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 informationLecture Slides. Elementary Statistics Tenth Edition. by Mario F. Triola. and the Triola Statistics Series. Slide 1
Lecture Slides Elementary Statistics Tenth Edition and the Triola Statistics Series by Mario F. Triola Slide 1 Chapter 6 Normal Probability Distributions 6-1 Overview 6-2 The Standard Normal Distribution
More informationThe Binomial Distribution
The Binomial Distribution Properties of a Binomial Experiment 1. It consists of a fixed number of observations called trials. 2. Each trial can result in one of only two mutually exclusive outcomes labeled
More informationChapter 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
More information8.1 Binomial Distributions
8.1 Binomial Distributions The Binomial Setting The 4 Conditions of a Binomial Setting: 1.Each observation falls into 1 of 2 categories ( success or fail ) 2 2.There is a fixed # n of observations. 3.All
More informationCounting Basics. Venn diagrams
Counting Basics Sets Ways of specifying sets Union and intersection Universal set and complements Empty set and disjoint sets Venn diagrams Counting Inclusion-exclusion Multiplication principle Addition
More informationStatistical 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***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,
More informationA 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
More informationDiscrete 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 information4.1 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
More informationChapter 6. The Normal Probability Distributions
Chapter 6 The Normal Probability Distributions 1 Chapter 6 Overview Introduction 6-1 Normal Probability Distributions 6-2 The Standard Normal Distribution 6-3 Applications of the Normal Distribution 6-5
More informationMA131 Lecture 9.1. = µ = 25 and σ X P ( 90 < X < 100 ) = = /// σ X
The Central Limit Theorem (CLT): As the sample size n increases, the shape of the distribution of the sample means taken with replacement from the population with mean µ and standard deviation σ will approach
More informationWeek 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 informationAP Statistics Chapter 6 - Random Variables
AP Statistics Chapter 6 - Random 6.1 Discrete and Continuous Random Objective: Recognize and define discrete random variables, and construct a probability distribution table and a probability histogram
More informationLab#3 Probability
36-220 Lab#3 Probability Week of September 19, 2005 Please write your name below, tear off this front page and give it to a teaching assistant as you leave the lab. It will be a record of your participation
More informationMA 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 informationECON 214 Elements of Statistics for Economists 2016/2017
ECON 214 Elements of Statistics for Economists 2016/2017 Topic Probability Distributions: Binomial and Poisson Distributions Lecturer: Dr. Bernardin Senadza, Dept. of Economics bsenadza@ug.edu.gh College
More informationExplanation on how to use to develop a sample plan or Answer question: How many samples should I take to ensure confidence in my data?
THE OPERATING CHARACTERISTIC CURVE (OC CURVE) The Operating characteristic curve is a picture of a sampling plan. Each sampling plan has a unique OC curve. The sample size and acceptance number define
More informationObjective: 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 informationSection 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
More informationConsider the following examples: ex: let X = tossing a coin three times and counting the number of heads
Overview Both chapters and 6 deal with a similar concept probability distributions. The difference is that chapter concerns itself with discrete probability distribution while chapter 6 covers continuous
More informationECON 214 Elements of Statistics for Economists
ECON 214 Elements of Statistics for Economists Session 7 The Normal Distribution Part 1 Lecturer: Dr. Bernardin Senadza, Dept. of Economics Contact Information: bsenadza@ug.edu.gh College of Education
More informationNormal Model (Part 1)
Normal Model (Part 1) Formulas New Vocabulary The Standard Deviation as a Ruler The trick in comparing very different-looking values is to use standard deviations as our rulers. The standard deviation
More informationBusiness Statistics Midterm Exam Fall 2013 Russell
Name SOLUTION Business Statistics Midterm Exam Fall 2013 Russell Do not turn over this page until you are told to do so. You will have 2 hours to complete the exam. There are a total of 100 points divided
More informationECON 214 Elements of Statistics for Economists 2016/2017
ECON 214 Elements of Statistics for Economists 2016/2017 Topic The Normal Distribution Lecturer: Dr. Bernardin Senadza, Dept. of Economics bsenadza@ug.edu.gh College of Education School of Continuing and
More informationA 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 informationDiscrete 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 informationChapter 8. Variables. Copyright 2004 Brooks/Cole, a division of Thomson Learning, Inc.
Chapter 8 Random Variables Copyright 2004 Brooks/Cole, a division of Thomson Learning, Inc. 8.1 What is a Random Variable? Random Variable: assigns a number to each outcome of a random circumstance, or,
More informationUsing the Central Limit
Using the Central Limit Theorem By: OpenStaxCollege It is important for you to understand when to use the central limit theorem. If you are being asked to find the probability of the mean, use the clt
More informationThe Normal Approximation to the Binomial
Lecture 16 The Normal Approximation to the Binomial We can calculate l binomial i probabilities bbilii using The binomial formula The cumulative binomial tables When n is large, and p is not too close
More informationStats 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
More informationChapter 6: Random Variables
Chapter 6: Random Variables Section 6.3 The Practice of Statistics, 4 th edition For AP* STARNES, YATES, MOORE Chapter 6 Random Variables 6.1 Discrete and Continuous Random Variables 6.2 Transforming and
More informationNormal Probability Distributions
C H A P T E R Normal Probability Distributions 5 Section 5.2 Example 3 (pg. 248) Normal Probabilities Assume triglyceride levels of the population of the United States are normally distributed with a mean
More informationChapter 4 Random Variables & Probability. Chapter 4.5, 6, 8 Probability Distributions for Continuous Random Variables
Chapter 4.5, 6, 8 Probability for Continuous Random Variables Discrete vs. continuous random variables Examples of continuous distributions o Uniform o Exponential o Normal Recall: A random variable =
More informationChapter 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 informationSTAT Chapter 5: Continuous Distributions. Probability distributions are used a bit differently for continuous r.v. s than for discrete r.v. s.
STAT 515 -- Chapter 5: Continuous Distributions Probability distributions are used a bit differently for continuous r.v. s than for discrete r.v. s. Continuous distributions typically are represented by
More informationMidterm Exam III Review
Midterm Exam III Review Dr. Joseph Brennan Math 148, BU Dr. Joseph Brennan (Math 148, BU) Midterm Exam III Review 1 / 25 Permutations and Combinations ORDER In order to count the number of possible ways
More information