Sec 5.2. Mean Variance Expectation. Bluman, Chapter 5 1
|
|
- Kristin Casey
- 5 years ago
- Views:
Transcription
1 Sec 5.2 Mean Variance Expectation Bluman, Chapter 5 1
2 Review: Do you remember the following? The symbols for Variance Standard deviation Mean The relationship between variance and standard deviation? Bluman, Chapter 5 2
3 5-2 Mean, Variance, Standard Deviation, and Expectation MEAN: X P X VARIANCE: X P X Bluman, Chapter 5 3
4 Mean, Variance, Standard Deviation, and Expectation Rounding Rule The mean, variance, and standard deviation should be rounded to one more decimal place than the outcome X. When fractions are used, they should be reduced to lowest terms. Bluman, Chapter 5 4
5 Chapter 5 Discrete Probability Distributions Section 5-2 Example 5-5 Page #260 Bluman, Chapter 5 5
6 Example 5-5: Rolling a Die Find the mean of the number of spots that appear when a die is tossed.. X P X Bluman, Chapter 5 6
7 Chapter 5 Discrete Probability Distributions Section 5-2 Example 5-8 Page #261 Bluman, Chapter 5 7
8 Example 5-8: Trips of 5 Nights or More The probability distribution shown represents the number of trips of five nights or more that American adults take per year. (That is, 6% do not take any trips lasting five nights or more, 70% take one trip lasting five nights or more per year, etc.) Find the mean.. Bluman, Chapter 5 8
9 Example 5-8: Trips of 5 Nights or More X P X Bluman, Chapter 5 9
10 Chapter 5 Discrete Probability Distributions Section 5-2 Example 5-9 Page #262 Bluman, Chapter 5 10
11 Example 5-9: Rolling a Die Compute the variance and standard deviation for the probability distribution in Example X P X , Bluman, Chapter 5 11
12 Chapter 5 Discrete Probability Distributions Section 5-2 Example 5-11 Page #263 Bluman, Chapter 5 12
13 Example 5-11: On Hold for Talk Radio A talk radio station has four telephone lines. If the host is unable to talk (i.e., during a commercial) or is talking to a person, the other callers are placed on hold. When all lines are in use, others who are trying to call in get a busy signal. The probability that 0, 1, 2, 3, or 4 people will get through is shown in the distribution. Find the variance and standard deviation for the distribution. Bluman, Chapter 5 13
14 Example 5-11: On Hold for Talk Radio , Bluman, Chapter 5 14
15 Example 5-11: On Hold for Talk Radio A talk radio station has four telephone lines. If the host is unable to talk (i.e., during a commercial) or is talking to a person, the other callers are placed on hold. When all lines are in use, others who are trying to call in get a busy signal. Should the station have considered getting more phone lines installed? Bluman, Chapter 5 15
16 Example 5-11: On Hold for Talk Radio No, the four phone lines should be sufficient. The mean number of people calling at any one time is 1.6. Since the standard deviation is 1.1, most callers would be accommodated by having four phone lines because µ + 2 would be (1.1) = = 3.8. Very few callers would get a busy signal since at least 75% of the callers would either get through or be put on hold. (See Chebyshev s theorem in Section 3 2.) Bluman, Chapter 5 16
17 Expectation The expected value, or expectation, of a discrete random variable of a probability distribution is the theoretical average of the variable. The expected value is, by definition, the mean of the probability distribution. E X X P X Bluman, Chapter 5 17
18 Chapter 5 Discrete Probability Distributions Section 5-2 Example 5-13 Page #265 Bluman, Chapter 5 18
19 Example 5-13: Winning Tickets One thousand tickets are sold at $1 each for four prizes of $100, $50, $25, and $10. After each prize drawing, the winning ticket is then returned to the pool of tickets. What is the expected value if you purchase two tickets? Gain X Probability P(X) $98 $48 $23 $8 - $ E X $98 $48 $ $8 $2 $ Bluman, Chapter 5 19
20 Example 5-13: Winning Tickets One thousand tickets are sold at $1 each for four prizes of $100, $50, $25, and $10. After each prize drawing, the winning ticket is then returned to the pool of tickets. What is the expected value if you purchase two tickets? Alternate Approach Gain X Probability P(X) $100 $50 $25 $10 $ E X $100 $50 $ $10 $0 $2 $ Bluman, Chapter 5 20
21 On Your Own: Technology Step by Step page 269 Exercises 5-2 Page 267 # 3,9,13 and 15 Bluman, Chapter 5 21
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
More informationMean, 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 informationMA 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 informationDay 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 informationLecture 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
More informationWhat 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 informationLecture 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
More informationDiscrete Random Variables
Discrete Random Variables MATH 130, Elements of Statistics I J. Robert Buchanan Department of Mathematics Fall 2017 Objectives During this lesson we will learn to: distinguish between discrete and continuous
More informationDiscrete Random Variables
Discrete Random Variables MATH 130, Elements of Statistics I J. Robert Buchanan Department of Mathematics Fall 2018 Objectives During this lesson we will learn to: distinguish between discrete and continuous
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 informationTOPIC: 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 informationUpcoming Schedule PSU Stat 2014
Upcoming Schedule PSU Stat 014 Monday Tuesday Wednesday Thursday Friday Jan 6 Sec 7. Jan 7 Jan 8 Sec 7.3 Jan 9 Jan 10 Sec 7.4 Jan 13 Chapter 7 in a nutshell Jan 14 Jan 15 Chapter 7 test Jan 16 Jan 17 Final
More informationMULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.
Module 5 Test Name MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Calculate the specified probability ) Suppose that T is a random variable. Given
More informationModule 4: Probability
Module 4: Probability 1 / 22 Probability concepts in statistical inference Probability is a way of quantifying uncertainty associated with random events and is the basis for statistical inference. Inference
More informationMath 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
More informationRefer to Ex 3-18 on page Record the info for Brand A in a column. Allow 3 adjacent other columns to be added. Do the same for Brand B.
Refer to Ex 3-18 on page 123-124 Record the info for Brand A in a column. Allow 3 adjacent other columns to be added. Do the same for Brand B. Test on Chapter 3 Friday Sept 27 th. You are expected to provide
More informationValue (x) probability Example A-2: Construct a histogram for population Ψ.
Calculus 111, section 08.x The Central Limit Theorem notes by Tim Pilachowski If you haven t done it yet, go to the Math 111 page and download the handout: Central Limit Theorem supplement. Today s lecture
More informationPart 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
More informationMATH1215: 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 informationExam II Math 1342 Capters 3-5 HCCS. Name
Exam II Math 1342 Capters 3-5 HCCS Name Date Provide an appropriate response. 1) A single six-sided die is rolled. Find the probability of rolling a number less than 3. A) 0.5 B) 0.1 C) 0.25 D 0.333 1)
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 informationguessing 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 informationCentral 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 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 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 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 informationExample - Let X be the number of boys in a 4 child family. Find the probability distribution table:
Chapter7 Probability Distributions and Statistics Distributions of Random Variables tthe value of the result of the probability experiment is a RANDOM VARIABLE. Example - Let X be the number of boys in
More informationSTA 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 informationExample - 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
More informationLearning Plan 3 Chapter 3
Learning Plan 3 Chapter 3 Questions 1 and 2 (page 82) To convert a decimal into a percent, you must move the decimal point two places to the right. 0.72 = 72% 5.46 = 546% 3.0842 = 308.42% Question 3 Write
More informationThe Binomial Distribution
MATH 382 The Binomial Distribution Dr. Neal, WKU Suppose there is a fixed probability p of having an occurrence (or success ) on any single attempt, and a sequence of n independent attempts is made. Then
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 informationDiscrete 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 informationLet 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
More informationL04: 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,
More informationDiscrete Random Variables
Discrete Random Variables In this chapter, we introduce a new concept that of a random variable or RV. A random variable is a model to help us describe the state of the world around us. Roughly, a RV can
More informationSection Random Variables and Histograms
Section 3.1 - Random Variables and Histograms 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 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 informationChapter 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.
More informationDiscrete Random Variables
Discrete Random Variables ST 370 A random variable is a numerical value associated with the outcome of an experiment. Discrete random variable When we can enumerate the possible values of the variable
More informationMATH 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 informationStatistics 511 Additional Materials
Discrete Random Variables In this section, we introduce the concept of a random variable or RV. A random variable is a model to help us describe the state of the world around us. Roughly, a RV can be thought
More information3.3-Measures of Variation
3.3-Measures of Variation Variation: Variation is a measure of the spread or dispersion of a set of data from its center. Common methods of measuring variation include: 1. Range. Standard Deviation 3.
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 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 informationShifting 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
More informationStatistics 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 informationCentral Limit Theorem
Central Limit Theorem Lots of Samples 1 Homework Read Sec 6-5. Discussion Question pg 329 Do Ex 6-5 8-15 2 Objective Use the Central Limit Theorem to solve problems involving sample means 3 Sample Means
More informationChapter 3: Probability Distributions and Statistics
Chapter 3: Probability Distributions and Statistics Section 3.-3.3 3. Random Variables and Histograms A is a rule that assigns precisely one real number to each outcome of an experiment. We usually denote
More informationA continuous random variable is one that can theoretically take on any value on some line interval. We use f ( x)
Section 6-2 I. Continuous Probability Distributions A continuous random variable is one that can theoretically take on any value on some line interval. We use f ( x) to represent a probability density
More information1. Steve says I have two children, one of which is a boy. Given this information, what is the probability that Steve has two boys?
Chapters 6 8 Review 1. Steve says I have two children, one of which is a boy. Given this information, what is the probability that Steve has two boys? (A) 1 (B) 3 1 (C) 3 (D) 4 1 (E) None of the above..
More informationExample. Chapter 8 Probability Distributions and Statistics Section 8.1 Distributions of Random Variables
Chapter 8 Probability Distributions and Statistics Section 8.1 Distributions of Random Variables You are dealt a hand of 5 cards. Find the probability distribution table for the number of hearts. Graph
More informationChapter 8 Homework Solutions Compiled by Joe Kahlig
homewk problems, B-copyright Joe Kahlig Chapter Solutions, Page Chapter omewk Solutions Compiled by Joe Kahlig 0. 0. 0. 0.. You are counting the number of games and there are a limited number of games
More informationTest 7A AP Statistics Name: Directions: Work on these sheets.
Test 7A AP Statistics Name: Directions: Work on these sheets. Part 1: Multiple Choice. Circle the letter corresponding to the best answer. 1. Suppose X is a random variable with mean µ. Suppose we observe
More informationSection 8.1 Distributions of Random Variables
Section 8.1 Distributions of Random Variables Random Variable A random variable is a rule that assigns a number to each outcome of a chance experiment. There are three types of random variables: 1. Finite
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 informationX P(X) (c) Express the event performing at least two tests in terms of X and find its probability.
AP Stats ~ QUIZ 6 Name Period 1. The probability distribution below is for the random variable X = number of medical tests performed on a randomly selected outpatient at a certain hospital. X 0 1 2 3 4
More informationHUDM4122 Probability and Statistical Inference. February 23, 2015
HUDM4122 Probability and Statistical Inference February 23, 2015 In the last class We studied Bayes Theorem and the Law of Total Probability Any questions or comments? Today Chapter 4.8 in Mendenhall,
More informationReview. 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 informationDiscrete Probability Distributions
blu0_ch0.qxd 09/4/00 :0 PM Page 7 C H A P T E R Discrete Probability Distributions Objectives Outline After completing this chapter, you should be able to Introduction Construct a probability distribution
More informationChapter 7 Study Guide: The Central Limit Theorem
Chapter 7 Study Guide: The Central Limit Theorem Introduction Why are we so concerned with means? Two reasons are that they give us a middle ground for comparison and they are easy to calculate. In this
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 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 informationExample 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
More informationBinomial 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 informationExercise Questions: Chapter What is wrong? Explain what is wrong in each of the following scenarios.
5.9 What is wrong? Explain what is wrong in each of the following scenarios. (a) If you toss a fair coin three times and a head appears each time, then the next toss is more likely to be a tail than a
More informationAP Statistics Review Ch. 6
AP Statistics Review Ch. 6 Name 1. Which of the following data sets is not continuous? a. The gallons of gasoline in a car. b. The time it takes to commute in a car. c. Number of goals scored by a hockey
More informationMATH FOR LIBERAL ARTS REVIEW 2
MATH FOR LIBERAL ARTS REVIEW 2 Use the theoretical probability formula to solve the problem. Express the probability as a fraction reduced to lowest terms. 1) A die is rolled. The set of equally likely
More informationLecture 8 - Sampling Distributions and the CLT
Lecture 8 - Sampling Distributions and the CLT Statistics 102 Kenneth K. Lopiano September 18, 2013 1 Basics Improvements 2 Variability of Estimates Activity Sampling distributions - via simulation Sampling
More informationUniform Probability Distribution. Continuous Random Variables &
Continuous Random Variables & What is a Random Variable? It is a quantity whose values are real numbers and are determined by the number of desired outcomes of an experiment. Is there any special Random
More information5.1 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
More informationTutorial 6. Sampling Distribution. ENGG2450A Tutors. 27 February The Chinese University of Hong Kong 1/6
Tutorial 6 Sampling Distribution ENGG2450A Tutors The Chinese University of Hong Kong 27 February 2017 1/6 Random Sample and Sampling Distribution 2/6 Random sample Consider a random variable X with distribution
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 information19. CONFIDENCE INTERVALS FOR THE MEAN; KNOWN VARIANCE
19. CONFIDENCE INTERVALS FOR THE MEAN; KNOWN VARIANCE We assume here that the population variance σ 2 is known. This is an unrealistic assumption, but it allows us to give a simplified presentation which
More informationLesson 4 Section 1.11, 1.13 Rounding Numbers Percent
Lesson 4 Section 1.11, 1.13 Rounding Numbers Percent Whole Number Place Value 0, 0 0 0, 0 0 0, 0 0 0, 0 0 0, 0 0 0, 0 0 0, 0 0 0 sextillions hundred quintillions ten quintillions quintillions hundred quadrillions
More informationList 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:
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 informationMath 227 Practice Test 2 Sec Name
Math 227 Practice Test 2 Sec 4.4-6.2 Name Find the indicated probability. ) A bin contains 64 light bulbs of which 0 are defective. If 5 light bulbs are randomly selected from the bin with replacement,
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 informationMath 14 Lecture Notes Ch. 4.3
4.3 The Binomial Distribution Example 1: The former Sacramento King's DeMarcus Cousins makes 77% of his free throws. If he shoots 3 times, what is the probability that he will make exactly 0, 1, 2, or
More informationStat 210 Exam Two. MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.
Stat 210 Exam Two Read these directions carefully. Take your time and check your work. Many students do not take enough time on their tests. Each problem is worth four points. You may choose exactly question
More informationData Analysis and Statistical Methods Statistics 651
Review of previous lecture: Why confidence intervals? Data Analysis and Statistical Methods Statistics 651 http://www.stat.tamu.edu/~suhasini/teaching.html Suhasini Subba Rao Suppose you want to know the
More informationA random variable is a quantitative variable that represents a certain
Section 6.1 Discrete Random Variables Example: Probability Distribution, Spin the Spinners Sum of Numbers on Spinners Theoretical Probability 2 0.04 3 0.08 4 0.12 5 0.16 6 0.20 7 0.16 8 0.12 9 0.08 10
More informationChapter 9. Sampling Distributions. A sampling distribution is created by, as the name suggests, sampling.
Chapter 9 Sampling Distributions 9.1 Sampling Distributions A sampling distribution is created by, as the name suggests, sampling. The method we will employ on the rules of probability and the laws of
More informationStatistical Methods for NLP LT 2202
LT 2202 Lecture 3 Random variables January 26, 2012 Recap of lecture 2 Basic laws of probability: 0 P(A) 1 for every event A. P(Ω) = 1 P(A B) = P(A) + P(B) if A and B disjoint Conditional probability:
More informationSTATISTICS - CLUTCH CH.9: SAMPLING DISTRIBUTIONS: MEAN.
!! www.clutchprep.com SAMPLING DISTRIBUTIONS (MEANS) As of now, the normal distributions we have worked with only deal with the population of observations Example: What is the probability of randomly selecting
More informationTelstra Thanks AFL Winning Feeling Moments Promotion Terms and Conditions
Telstra Thanks AFL Winning Feeling Moments Promotion Terms and Conditions 1. Information on how to enter and prize details form part of these Telstra Thanks AFL Winning Feeling Moments Promotion Terms
More informationA random variable X is a function that assigns (real) numbers to the elements of the sample space S of a random experiment.
RANDOM VARIABLES and PROBABILITY DISTRIBUTIONS A random variable X is a function that assigns (real) numbers to the elements of the samle sace S of a random exeriment. The value sace V of a random variable
More informationChapter 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
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 informationMULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question.
AP Stats: Test Review - Chapters 16-17 Name Period MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. Find the expected value of the random variable.
More informationSection 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 informationChapter 5. Sampling Distributions
Lecture notes, Lang Wu, UBC 1 Chapter 5. Sampling Distributions 5.1. Introduction In statistical inference, we attempt to estimate an unknown population characteristic, such as the population mean, µ,
More informationName: Date: Pd: Quiz Review
Name: Date: Pd: Quiz Review 8.1-8.3 Multiple Choice Identify the choice that best completes the statement or answers the question. 1. A die is cast repeatedly until a 1 falls uppermost. Let the random
More informationThe 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.
More informationOCR 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 informationConfidence Intervals: Review
University of Utah February 28, 2018 1 2 Law of Large Numbers Draw your samples from any population with finite mean µ. Then LLN says Law of Large Numbers Draw your samples from any population with finite
More informationChapter 6. Percents and their Applications
Chapter 6 Percents and their Applications What is a percent? A percent is 1 one hundredth of a number. For instance, a penny is 1/100 of a dollar. Each one hundredth is 1% A nickel is 5/100 of a dollar
More informationRandom variables. Discrete random variables. Continuous random variables.
Random variables Discrete random variables. Continuous random variables. Discrete random variables. Denote a discrete random variable with X: It is a variable that takes values with some probability. Examples:
More informationMA : 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