If X = the different scores you could get on the quiz, what values could X be?
|
|
- Isabella Burns
- 6 years ago
- Views:
Transcription
1 Example 1: Quiz? Take it. o, there are no questions m giving you. You just are giving me answers and m telling you if you got the answer correct. Good luck: hope you studied! Circle the correct answers that were read to you. Give yourself a score out of 5: Did you pass? f X = the different scores you could get on the quiz, what values could X be? X: score Probability Using your method of choice, simulate taking the quiz 10 more times, and add your 10 scores to the table. When all the scores have been totaled, we will complete our probability distribution in the table. According to our distribution, if we were to take the quiz by guessing, what is the most likely score? This assumption is based on our probability distribution of simulations, not a theoretical distribution. Getting a question right or wrong is an example of a binomial random variable For a variable to be considered which is only for variables, it has to meet the following conditions:? Each trial can result in just two possible outcomes. We call one of these outcomes a and the other, a.? The trials are independent; that is, the outcome on one trial does not affect the outcome on other trials.? The number of trials n of the chance process must be in advance.? The probability of success, denoted by, is the same on every trial.
2 Example 2: Determine if the given random variable has a binomial distribution. Explain your response. Consider the following statistical experiments. Using, are they binomial? 1. huffle a deck of cards. Turn over the top card. Put the card back in the deck, and shuffle again. Repeat this process 10 times. Let X = the number of aces you observe. 2. Choose three students at random from your class. Let Y = the number who are over 6 feet tall. 3. Flip a coin. f it s heads, roll a 6-sided die. f it s tails, roll an 8-sided die. Repeat this process 5 times. Let W = the number of 5s you roll. 4. You are taking a 5-question quiz by guessing. Let C = the number of problems you get correct.
3 Example 3: Our guessing quiz Hey, #4 looks familiar. o now that we know that our quiz-taking is an example of a binomial distribution, what does the theoretical probability distribution look like? X: score Probability To find the probabilities, we have to use the multiplication rule, since these events are independent. a. What would the probability be that we guess none of them correctly? P(X=0) Question 1 question 2 question 3 question 4 question 5 b. What would the probability be that we guess all of them correctly? P(X=5) = Question 1 question 2 question 3 question 4 question 5 c. What would the probability be that we guess exactly one correctly? P(X=1) = This one is more complicated because unlike a and b, there are multiple ways to guess only one problem correctly. d. Create the sample space to show how many ways there are to guess one problem correctly on a five-question quiz.
4 e. What is the probability for guessing exactly 2 correctly? Formula for binomial probability n = k = p = 1-p = The n over k in the parenthesis is called the which is the number of ways an event can happen, and is calculated using combinations,. o let s try it: e. What is the probability for guessing exactly 2 correctly? P(X=2): et up your equation using the formula, with n = k = p = 1 p = Value of binomial coefficient: (on your calculator, type in your value of n, 5, then Math, Prb, 3:nCr, and 2, since k = 2): f. Use the formula to complete our probability distribution, table and graph.
5 Example 4: 1 in 6 wins! As a special promotion for its 20-ounce bottles of soda, a soft drink company printed a message on the inside of each cap. ome of the caps said, Please try again, while others said, You re a winner! The company advertised the promotion with the slogan 1 in 6 wins a prize. even friends each buy one 20-ounce bottle at a local convenience store. The store clerk is surprised when three of them win a prize. s this group of friends just lucky, or is the company s 1 in 6 claim inaccurate? inomial setting: How to use your T calculator to calculate binomial probabilities inomial random variable: X = Probability distribution: Feel free to use, but in order to get credit on a test, want to see the set up using the formula nd /VAR 2. croll down a. inompdf(n,p,k): used when finding P(X = k) b. inomcdf(n,p,k): used when finding P(X k) i. Careful using the binomcdf it can be misleading when you want to use it to find instead P(X k). n these cases, make sure to find 1-P(X k-1) instead of 1-P(X k). Make a list of desired outcomes to be sure. f you don t specify X, it will give you the probability for all values of X, from 0 to n as a list Value Probability hape: Center: pread: P(X 3) =
6 Example 5: Thinking again about that quiz a. How many questions of the 5 do you think you would expect to get correct? This is the mean of this particular binomial distribution. Mean and standard deviation of a binomial random variable b. Calculate the standard deviation of this distribution. μx= σx= c. Find the mean and standard deviation for the 1 in 6 wins example. Example 6: Tastes as Good as the Real Thing? The makers of a diet cola claim that its taste is indistinguishable from the full calorie version of the same cola. To investigate, an AP tatistics student named Emily prepared small samples of each type of soda in identical cups. Then, she had volunteers taste each cola in a random order and try to identify which was the diet cola and which was the regular cola. Overall, 23 of the 30 subjects made the correct identification. f we assume that the volunteers really couldn t tell the difference, then each one was guessing with a 1/2 chance of being correct. Let X = the number of volunteers who correctly identify the colas. Problem: (a) Explain why X is a binomial random variable. (b) Find the mean and the standard deviation of X. nterpret each value in context. (c) Of the 30 volunteers, 23 made correct identifications. Does this give convincing evidence that the volunteers can taste the difference between the diet and regular colas?
Chapter 6: Random Variables. Ch. 6-3: Binomial and Geometric Random Variables
Chapter : Random Variables Ch. -3: Binomial and Geometric Random Variables X 0 2 3 4 5 7 8 9 0 0 P(X) 3???????? 4 4 When the same chance process is repeated several times, we are often interested in whether
More informationBinomial 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
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 informationCHAPTER 6 Random Variables
CHAPTER 6 Random Variables 6.3 Binomial and Geometric Random Variables The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers Binomial and Geometric Random
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 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 informationCHAPTER 6 Random Variables
CHAPTER 6 Random Variables 6.3 Binomial and Geometric Random Variables The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers 6.3 Reading Quiz (T or F) 1.
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 informationProbability & 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
More informationMATH 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
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 informationRandom Variables CHAPTER 6.3 BINOMIAL AND GEOMETRIC RANDOM VARIABLES
Random Variables CHAPTER 6.3 BINOMIAL AND GEOMETRIC RANDOM VARIABLES Essential Question How can I determine whether the conditions for using binomial random variables are met? Binomial Settings When the
More informationMath 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
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 informationDO NOT POST THESE ANSWERS ONLINE BFW Publishers 2014
Section 6.3 Check our Understanding, page 389: 1. Check the BINS: Binary? Success = get an ace. Failure = don t get an ace. Independent? Because you are replacing the card in the deck and shuffling each
More informationThe following content is provided under a Creative Commons license. Your support
MITOCW Recitation 6 The following content is provided under a Creative Commons license. Your support will help MIT OpenCourseWare continue to offer high quality educational resources for free. To make
More informationCHAPTER 4 DISCRETE PROBABILITY DISTRIBUTIONS
CHAPTER 4 DISCRETE PROBABILITY DISTRIBUTIONS A random variable is the description of the outcome of an experiment in words. The verbal description of a random variable tells you how to find or calculate
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 informationBinomial 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),
More informationWhat 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.
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 informationTest 6A AP Statistics Name:
Test 6A AP Statistics Name: Part 1: Multiple Choice. Circle the letter corresponding to the best answer. 1. A marketing survey compiled data on the number of personal computers in households. If X = the
More 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 informationRandom Variables. Chapter 6: Random Variables 2/2/2014. Discrete and Continuous Random Variables. Transforming and Combining Random Variables
Chapter 6: Random Variables Section 6.3 The Practice of Statistics, 4 th edition For AP* STARNES, YATES, MOORE Random Variables 6.1 6.2 6.3 Discrete and Continuous Random Variables Transforming and Combining
More informationStats CH 6 Intro Activity 1
Stats CH 6 Intro Activit 1 1. Purpose can ou tell the difference between bottled water and tap water? You will drink water from 3 samples. 1 of these is bottled water.. You must test them in the following
More informationCHAPTER 6 Random Variables
CHAPTER 6 Random Variables 6.3 Binomial and Geometric Random Variables The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers Binomial and Geometric Random
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 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 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 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 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 informationChapter 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
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 informationSection M Discrete Probability Distribution
Section M Discrete Probability Distribution A random variable is a numerical measure of the outcome of a probability experiment, so its value is determined by chance. Random variables are typically denoted
More 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 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 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 informationChapter 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
More informationII - Probability. Counting Techniques. three rules of counting. 1multiplication rules. 2permutations. 3combinations
II - Probability Counting Techniques three rules of counting 1multiplication rules 2permutations 3combinations Section 2 - Probability (1) II - Probability Counting Techniques 1multiplication rules In
More informationBinomial and Normal Distributions. Example: Determine whether the following experiments are binomial experiments. Explain.
Binomial and Normal Distributions Objective 1: Determining if an Experiment is a Binomial Experiment For an experiment to be considered a binomial experiment, four things must hold: 1. The experiment is
More 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 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 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 informationSTAT 201 Chapter 6. Distribution
STAT 201 Chapter 6 Distribution 1 Random Variable We know variable Random Variable: a numerical measurement of the outcome of a random phenomena Capital letter refer to the random variable Lower case letters
More informationExperimental Probability - probability measured by performing an experiment for a number of n trials and recording the number of outcomes
MDM 4U Probability Review Properties of Probability Experimental Probability - probability measured by performing an experiment for a number of n trials and recording the number of outcomes Theoretical
More informationVIDEO 1. A random variable is a quantity whose value depends on chance, for example, the outcome when a die is rolled.
Part 1: Probability Distributions VIDEO 1 Name: 11-10 Probability and Binomial Distributions A random variable is a quantity whose value depends on chance, for example, the outcome when a die is rolled.
More informationMATH 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
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 information3. The n observations are independent. Knowing the result of one observation tells you nothing about the other observations.
Binomial and Geometric Distributions - Terms and Formulas Binomial Experiments - experiments having all four conditions: 1. Each observation falls into one of two categories we call them success or failure.
More informationChapter 6 Section 3: Binomial and Geometric Random Variables
Name: Date: Period: Chapter 6 Section 3: Binomial and Geometric Random Variables When the same chance process is repeated several times, we are often interested whether a particular outcome does or does
More information6.1 Binomial Theorem
Unit 6 Probability AFM Valentine 6.1 Binomial Theorem Objective: I will be able to read and evaluate binomial coefficients. I will be able to expand binomials using binomial theorem. Vocabulary Binomial
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 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 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 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 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 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 information12 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.
More informationPart 10: The Binomial Distribution
Part 10: The Binomial Distribution The binomial distribution is an important example of a probability distribution for a discrete random variable. It has wide ranging applications. One readily available
More 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 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 informationChapter 6 Probability
Chapter 6 Probability Learning Objectives 1. Simulate simple experiments and compute empirical probabilities. 2. Compute both theoretical and empirical probabilities. 3. Apply the rules of probability
More information3. The n observations are independent. Knowing the result of one observation tells you nothing about the other observations.
Binomial and Geometric Distributions - Terms and Formulas Binomial Experiments - experiments having all four conditions: 1. Each observation falls into one of two categories we call them success or failure.
More informationChapter 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
More informationand their probabilities p
AP Statistics Ch. 6 Notes Random Variables A variable is any characteristic of an individual (remember that individuals are the objects described by a data set and may be eole, animals, or things). Variables
More informationSTT315 Chapter 4 Random Variables & Probability Distributions AM KM
Before starting new chapter: brief Review from Algebra Combinations In how many ways can we select x objects out of n objects? In how many ways you can select 5 numbers out of 45 numbers ballot to win
More informationAP Statistics Section 6.1 Day 1 Multiple Choice Practice. a) a random variable. b) a parameter. c) biased. d) a random sample. e) a statistic.
A Statistics Section 6.1 Day 1 ultiple Choice ractice Name: 1. A variable whose value is a numerical outcome of a random phenomenon is called a) a random variable. b) a parameter. c) biased. d) a random
More 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 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 informationSimple 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.
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 informationLesson 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
More informationOpening 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
More informationSolutions for practice questions: Chapter 15, Probability Distributions If you find any errors, please let me know at
Solutions for practice questions: Chapter 15, Probability Distributions If you find any errors, please let me know at mailto:msfrisbie@pfrisbie.com. 1. Let X represent the savings of a resident; X ~ N(3000,
More informationSolution: 7525 = t Subtract 4300 from both sides to get 3225 = 215t = t = 15. It will take 15 years.
1. You have $2500 that you invest at 6% simple interest. What is the balance after four years? A = 2500 + 2500 0.06 4 = 3100 2. You have $7000 that you invest at 9% simple interest. What is the balance
More information23.1 Probability Distributions
3.1 Probability Distributions Essential Question: What is a probability distribution for a discrete random variable, and how can it be displayed? Explore Using Simulation to Obtain an Empirical Probability
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 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 informationBinomial and multinomial distribution
1-Binomial distribution Binomial and multinomial distribution The binomial probability refers to the probability that a binomial experiment results in exactly "x" successes. The probability of an event
More informationFINAL REVIEW W/ANSWERS
FINAL REVIEW W/ANSWERS ( 03/15/08 - Sharon Coates) Concepts to review before answering the questions: A population consists of the entire group of people or objects of interest to an investigator, while
More informationEXERCISES ACTIVITY 6.7
762 CHAPTER 6 PROBABILITY MODELS EXERCISES ACTIVITY 6.7 1. Compute each of the following: 100! a. 5! I). 98! c. 9P 9 ~~ d. np 9 g- 8Q e. 10^4 6^4 " 285^1 f-, 2 c 5 ' sq ' sq 2. How many different ways
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 informationChapter 5. Discrete Probability Distributions. Random Variables
Chapter 5 Discrete Probability Distributions Random Variables x is a random variable which is a numerical description of the outcome of an experiment. Discrete: If the possible values change by steps or
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 Accuracy of Percentages. Confidence Intervals
The Accuracy of Percentages Confidence Intervals 1 Review: a 0-1 Box Box average = fraction of tickets which equal 1 Box SD = (fraction of 0 s) x (fraction of 1 s) 2 With a simple random sample, the expected
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 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 informationThe Binomial Distribution
The Binomial Distribution January 31, 2018 Contents The Binomial Distribution The Normal Approximation to the Binomial The Binomial Hypothesis Test Computing Binomial Probabilities in R 30 Problems The
More informationProbability 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
More informationAP Statistics Quiz A Chapter 17
AP Statistics Quiz A Chapter 17 Name The American Red Cross says that about 11% of the U.S. population has Type B blood. A blood drive is being held at your school. 1. How many blood donors should the
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 informationThe Binomial Distribution
The Binomial Distribution January 31, 2019 Contents The Binomial Distribution The Normal Approximation to the Binomial The Binomial Hypothesis Test Computing Binomial Probabilities in R 30 Problems The
More information8.1 Binomial Situations
8.1 Binomial Situations "Dumb Dora" didn't study for her final exam. It was a true/false test, so she decided to flip a coin for the answers. The statistics professor watched her the entire two hours as
More information***SECTION 7.1*** Discrete and Continuous Random Variables
***SECTION 7.1*** Discrete and Continuous Random Variables UNIT 6 ~ Random Variables Sample spaces need not consist of numbers; tossing coins yields H s and T s. However, in statistics we are most often
More informationMath 243 Section 4.3 The Binomial Distribution
Math 243 Section 4.3 The Binomial Distribution Overview Notation for the mean, standard deviation and variance The Binomial Model Bernoulli Trials Notation for the mean, standard deviation and variance
More 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 informationHonors Statistics. Aug 23-8:26 PM. 1. Collect folders and materials. 2. Continue Binomial Probability. 3. Review OTL C6#11 homework
Honors Statistics Aug 23-8:26 PM 1. Collect folders and materials 2. Continue Binomial Probability 3. Review OTL C6#11 homework 4. Binomial mean and standard deviation 5. Past Homework discussion 6. Return
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 informationx is a random variable which is a numerical description of the outcome of an experiment.
Chapter 5 Discrete Probability Distributions Random Variables is a random variable which is a numerical description of the outcome of an eperiment. Discrete: If the possible values change by steps or jumps.
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 information