"What Are Examples Of Variables That Follow A Binomial Probability Distribution" Essays and Research Papers

  • What Are Examples Of Variables That Follow A Binomial Probability Distribution

    Probability distribution Definition with example: The total set of all the probabilities of a random variable to attain all the possible values. Let me give an example. We toss a coin 3 times and try to find what the probability of obtaining head is? Here the event of getting head is known as the random variable. Now what are the possible values of the random variable, i.e. what is the possible number of times that head might occur? It is 0 (head never occurs), 1 (head occurs once out of 2 tosses)...

    Cumulative distribution function, Discrete probability distribution, Probability and statistics 803  Words | 3  Pages

  • Probability distribution

     _____ 1. What is mean, variance and expectations? Mean - The mean of a discrete random variable X is a weighted average of the possible values that the random variable can take. Unlike the sample mean of a group of observations, which gives each observation equal weight, the mean of a random variable weights each outcome xi according to its probability, pi. The mean also of a random variable provides the long-run average of the variable, or the expected average outcome over...

    Arithmetic mean, Binomial distribution, Discrete probability distribution 710  Words | 3  Pages

  • Binomial Probability Distribution

    we cannot always use the normal approximation to binomial. Solution: If a sample is n>30, we can say that sample size is sufficiently large to assume normal approximation to binomial curve. Hence the statement is false. #2 A salesperson goes door-to-door in a residential area to demonstrate the use of a new Household appliance to potential customers. She has found from her years of experience that after demonstration, the probability of purchase (long run average) is 0.30. To perform...

    Binomial distribution, Customer service, Door-to-door 807  Words | 6  Pages

  • Probability Theory and Random Variable

    are infected. What is the probability that 3 randomly chosen client computers serviced by different servers (one per server) will all be infected? The probability that Alice’s RSA signature on a document is forged is () What is the probability that out of 4 messages sent by Alice to Bob at least one is not forged? Event A is selecting a “red” card from a standard deck at random. Suggest another event (Event B) that is compatible with Event A. What is the probability of getting 6 tails...

    Cumulative distribution function, Moment, Normal distribution 951  Words | 2  Pages

  • Discrete Probability Distribution and Standard Deck

    EXERCISES (Discrete Probability Distribution) EXERCISES (Discrete Probability Distribution) P X  x    n C x  p  1  p  x BINOMIAL DISTRIBUTION n x P X  x    n C x  p  1  p  x BINOMIAL DISTRIBUTION n x 1. 2. 3. The probability that a certain kind of component will survive a given shock test is ¾. Find the probability that exactly 2 of the next 4 components tested survive. The probability that a log-on to the network is successful is 0.87. Ten users...

    Binomial distribution, Discrete probability distribution, Geometric distribution 1459  Words | 6  Pages

  • Distribution Assignment

    Assignment Q1Find the parameters of binomial distribution when mean=4 and variance=3. Q2. The output of a production process is 10% defective. What is the probability of selecting exactly two defectives in a sample of 5? Q3. It is observed that 80% of television viewers watch “Boogie-Woogie” Programme. What is the probability that at least 80% of the viewers in a random sample of five watch this Programme? Q4. The normal rate of infection of a certain disease in animals is known to...

    Binomial distribution, Cauchy distribution, Cumulative distribution function 988  Words | 4  Pages

  • Probability Theory and Ans

    Classify the following random variable as to whether it is discrete or continuous. 1) The number of runs scored in a baseball game. A) continuous B) discrete Ans = B 2) The cost of a road map. A) continuous B) discrete Ans = B Provide an appropriate response. 3) A random variable is A) generated by a random number table. B) the variable for which an algebraic equation is solved. C) a numerical measure of a probability experiment.. Ans...

    Binomial distribution, Cumulative distribution function, Normal distribution 651  Words | 3  Pages

  • Tutorial on Discrete Probability Distributions.

    Tutorial on Discrete Probability Distributions Tutorial on discrete probability distributions with examples and detailed solutions. ------------------------------------------------- Top of Form |  Web |  www.analyzemath.com | | Bottom of Form | | Let X be a random variable that takes the numerical values X1, X2, ..., Xn with probablities p(X1), p(X2), ..., p(Xn) respectively. A discrete probability distribution consists of the values of the random variable X and their corresponding...

    Continuous probability distribution, Discrete probability distribution, Probability and statistics 911  Words | 4  Pages

  • Poisson Distribution

    Poisson distribution is a discrete distribution. It is often used as a model for the number of events (such as the number of telephone calls at a business, number of customers in waiting lines, number of defects in a given surface area, airplane arrivals, or the number of accidents at an intersection) in a specific time period. It is also useful in ecological studies, e.g., to model the number of prairie dogs found in a square mile of prairie. The major difference between Poisson and Binomial distributions...

    Arithmetic mean, Average, Binomial distribution 754  Words | 3  Pages

  • Binomial Distribution

    The Binomial Distribution October 20, 2010 The Binomial Distribution Bernoulli Trials Definition A Bernoulli trial is a random experiment in which there are only two possible outcomes - success and failure. 1 Tossing a coin and considering heads as success and tails as failure. The Binomial Distribution Bernoulli Trials Definition A Bernoulli trial is a random experiment in which there are only two possible outcomes - success and failure. 1 Tossing a coin and considering...

    Bernoulli distribution, Bernoulli trial, Binomial distribution 2027  Words | 10  Pages

  • Probability

    PROBABILITY DISTRIBUTION In the world of statistics, we are introduced to the concept of probability. On page 146 of our text, it defines probability as "a value between zero and one, inclusive, describing the relative possibility (chance or likelihood) an event will occur" (Lind, 2012). When we think about how much this concept pops up within our daily lives, we might be shocked to find the results. Oftentimes, we do not think in these terms, but imagine what the probability of us getting behind...

    Continuous probability distribution, Discrete probability distribution, Jesus 1089  Words | 3  Pages

  • Random Variable and Standard Deviation

    MATH 107 NAME:_______________________ EXAM 2 Show all work for credit and keep answers exact when possible. 1. Classify the following statement as an example of classical, empirical, or subjective probability and explain your reasoning. According to your doctor he feels the chance of you surviving a surgery is 0.85. Subjective; based upon his feelings. 2. Determine the two events described in the study. Do the results indicate that the events are independent or dependant? ...

    Cumulative distribution function, Discrete probability distribution, Probability 560  Words | 3  Pages

  • Normal Distribution

    NORMAL DISTRIBUTION 1. Find the distribution: a. b. c. d. e. f. following probabilities, the random variable Z has standard normal P (0< Z < 1.43) P (0.11 < Z < 1.98) P (-0.39 < Z < 1.22) P (Z < 0.92) P (Z > -1.78) P (Z < -2.08) 2. Determine the areas under the standard normal curve between –z and +z: ♦ z = 0.5 ♦ z = 2.0 Find the two values of z in standard normal distribution so that: P(-z < Z < +z) = 0.84 3. At a university, the average height of 500 students of a course is 1.70 m; the standard...

    Binomial distribution, Cumulative distribution function, Normal distribution 982  Words | 3  Pages

  • Probability

    CHAPTER 3: PROBABILITY DISTRIBUTION 3.1 RANDOM VARIABLES AND PROBABILITY DISTRIBUTION Random variables is a quantity resulting from an experiment that, by chance, can assume different values. Examples of random variables are the number of defective light bulbs produced during the week and the heights of the students is a class. Two types of random variables are discrete random variables and continuous random variable. 3.2 DISCRETE RANDOM VARIABLE A random variable is called a discrete...

    Continuous probability distribution, Cumulative distribution function, Discrete probability distribution 612  Words | 4  Pages

  • Binomial Theorem

    BINOMIAL THEOREM :  AKSHAY MISHRA XI A , K V 2 , GWALIOR In elementary algebra, the binomial theorem describes the algebraic expansion of powers of a binomial. According to the theorem, it is possible to expand the power (x + y)n into a sum involving terms of the form axbyc, where the coefficient of each term is a positive integer, and the sum of the exponents of x and y in each term is n. For example: The coefficients appearing in the binomial expansion are known as binomial coefficients....

    Algebra, Binomial, Binomial coefficient 1409  Words | 4  Pages

  • Normal Distribution, Solved Problems

    Unit 6. Normal Distribution Solution to problems Statistics I. International Group Departamento de Economa Aplicada Universitat de Valncia May 20, 2010 Problem 35 Random variable X : weekly ticket sales (units) of a museum. X ∼ N(1000, 180) Find the probability of weekly sales exceeding 850 tickets. Find the probability of the interval 1000 to 1200 Take 5 weeks at random. Find the probability of weekly sales not exceeding 850 tickets in more than two weeks Ticket price is 4.5 Euros...

    Cumulative distribution function, Discrete probability distribution, Normal distribution 1015  Words | 4  Pages

  • Lab 03 Normal Distribution

     PGEG371: Data Analysis & Geostatistics Normal Distributions Laboratory Exercise # 3 1st and 5th February, 2015 Read through this instruction sheet then answer the ‘pre-Lab’ quiz BEFORE starting the exercises! 1. Aim The purpose of this laboratory exercise is to use a Normal Distribution to find information about a data population. On successful completion of this exercise, you should be able to Describe what a Normal Distribution is; How the histogram for a whole population looks...

    Cumulative distribution function, Normal distribution, Probability density function 1215  Words | 8  Pages

  • Probability And Statistics

    AAOC ZC111 : Probability and Statistics Course E-mail address : aaoczc111@dlpd.bits-pilani.ac.in Course Description Probability spaces; conditional probability and independence; random variables and probability distributions; marginal and conditional distributions; independent random variables, mathematical exceptions, mean and variance, Binomial Poisson and normal distribution; sum of independent random variables; law of large numbers; central limit theorem; sampling distributions; tests for mean...

    Discrete probability distribution, Normal distribution, Probability 707  Words | 2  Pages

  • Chap05 Discrete Probability Distribution

    Important Discrete Probability Distributions 5-1 Chapter Goals After completing this chapter, you should be able to:  Interpret the mean and standard deviation for a discrete probability distribution  Explain covariance and its application in finance  Use the binomial probability distribution to find probabilities  Describe when to apply the binomial distribution  Use Poisson discrete probability distributions to find probabilities 5-2 Definitions Random Variables  A random variable represents...

    Binomial distribution, Continuous probability distribution, Discrete probability distribution 2676  Words | 50  Pages

  • Probability Theory

    for the Binomial Distribution P(S) The symbol for the probability of success P(F) The symbol for the probability of failure p The numerical probability of a success q The numerical probability of a failure P(S) = p and P(F) = 1 - p = q n The number of trials X The number of successes The probability of a success in a binomial experiment can be computed with the following formula. Binomial Probability...

    Binomial distribution, Binomial probability, Binomial theorem 751  Words | 4  Pages

  • Binomial, Bernoulli and Poisson Distributions

    Binomial, Bernoulli and Poisson Distributions The Binomial, Bernoulli and Poisson distributions are discrete probability distributions in which the values that might be observed are restricted to being within a pre-defined list of possible values. This list has either a finite number of members, or at most is countable. * Binomial distribution In many cases, it is appropriate to summarize a group of independent observations by the number of observations in the group that represent one of...

    Bernoulli distribution, Binomial distribution, Discrete probability distribution 493  Words | 2  Pages

  • Decision Theory and Probability Distributions

    North Star Concert North Star.xls Best Guess, Worst Case, Best Case; and Continuous Uncertainties 3 Engine Services, Inc. Quick Start Guide to Crystal Ball Analyzing Uncertainty, Probability Distributions, and Simulation Learning Module: Crystal Ball Litigate Demo Engine Services.xls Language of Probability Distributions and Monte Carlo Simulation 4 Taurus Telecommunications Corporation: A New Prepaid Phone Card Learning Module: Tornado Sensitivity Taurus Telecommunications.xls Sensitivity Analysis...

    Cumulative distribution function, Decision theory, Decision tree 469  Words | 3  Pages

  • Probability Exercice

    at random. What is the probability that at least one pair of shoes is obtained? 2. At a camera factory, an inspector checks 20 cameras and finds that three of them need adjustment before they can be shipped. Another employee carelessly mixes the cameras up so that no one knows which is which. Thus, the inspector must recheck the cameras one at a time until he locates all the bad ones. (a) What is the probability that no more than 17 cameras need to be rechecked? (b) What is the probability that exactly...

    Cumulative distribution function, Discrete probability distribution, Probability 2054  Words | 6  Pages

  • Random Variable and Probability Distribution Function

    Chapter 3 Probability Distributions 1. Based on recent records, the manager of a car painting center has determined the following probability distribution for the number of customers per day. Suppose the center has the capacity to serve two customers per day. |x |P(X = x) | |0 |0.05 | |1 |0.20 | |2 |0.30 | |3 |0.25 | |4 |0.15 | |5 |0.05 | a. What is the probability that one...

    Arithmetic mean, Normal distribution, Probability density function 5518  Words | 19  Pages

  • Discrete Random Variables

    Modelling 2 Week 3: Discrete Random Variables Stephen Bush Department of Mathematical Sciences MM2: Statistics - Week 3 - 1 Random Variables • Reference: Devore § 3.1 – 3.5 • Definitions: • An experiment is any process of obtaining one outcome where the outcome is uncertain. • A random variable is a numerical variable whose value can change from one replicate of the experiment to another. • Sample means and sample standard deviations are random variables • They are different from sample...

    Cumulative distribution function, Discrete probability distribution, Normal distribution 1322  Words | 9  Pages

  • The T-Distribution and T-Test

    The T-Distribution and T-Test “In probability and statistics, Student's t-distribution (or simply the t-distribution) is a continuous probability distribution that arises when estimating the mean of a normally distributed population in situations where the sample size is small” (Narasimhan , 1996). Similar to the normal distribution, the t-distribution is symmetric and bell-shaped, but has heavier tails, meaning that it is more likely to produce values far from its mean. This makes the t-distribution...

    Confidence interval, Normal distribution, Sample size 1244  Words | 4  Pages

  • Normal Distribution

     Normal Distribution Normal distribution is a statistics, which have been widely applied of all mathematical concepts, among large number of statisticians. Abraham de Moivre, an 18th century statistician and consultant to gamblers, noticed that as the number of events (N) increased, the distribution approached, forming a very smooth curve. He insisted that a new discovery of a mathematical expression for this curve could lead to an easier way to find solutions...

    Cumulative distribution function, Moment, Normal distribution 1225  Words | 5  Pages

  • Descriptive Statistics and Probability Distribution Problem Sets

    Descriptive Statistics and Probability Distribution Problem Sets Emily Noah QNT561 Anthony Matias December 24, 2012 Descriptive Statistics and Probability Distribution Problems Sets Descriptive statistics and probability distribution is two ways to find information with certain data giving. In Descriptive statistics the data can give a mode, mean, median, and range by the numerical information, which is giving to find the information. In probability distribution the data is collected and...

    Arithmetic mean, Data, Mean 765  Words | 3  Pages

  • special prob distribution

    Special Probability Distributions Chapter 8 Ibrahim Bohari bibrahim@preuni.unimas.my LOGO Binomial Distribution Binomial Distribution In an experiment of n independent trials, where p is a the probability of a successful outcome q=1-p is the probability that the outcome is a failure If X is a random variable denoting the number of successful outcome, the probability function of X is given P X  r  nCr p r q nr Where q=1-p r=0,1,2,3,….. X~B(n,p) The n trials...

    Cumulative distribution function, Normal distribution, Probability density function 2079  Words | 20  Pages

  • Sampling Distribution of the Sample Mean

    PROBABILITY AND STATISTICS Lab, Seminar, Lecture 4. Behavior of the sample average X-bar  The topic of 4th seminar&lab is the average of the population that has a certain characteristic.  This average is the population parameter of interest, denoted by the greek letter mu.  We estimate this parameter with the statistic x-bar, the average in the sample. Probability and statistics - Karol Flisikowski X-bar Definition 1 x   xi n i 1 Probability and statistics - Karol Flisikowski ...

    Arithmetic mean, Central limit theorem, Normal distribution 503  Words | 3  Pages

  • Random Variable and Binomial Setting

    8.1 BINOMIAL SETTING? In each situation below, is it reasonable to use a binomial distribution for the random variable X? Give reasons for your answer in each case. (a) An auto manufacturer chooses one car from each hour’s production for a detailed quality inspection. One variable recorded is the count X of finish defects (dimples, ripples, etc.) in the car’s paint. No: There is no fixed n (i.e., there is no definite upper limit on the number of defects). (b) The pool of potential jurors for...

    Customer, Customer service, Discrete probability distribution 430  Words | 2  Pages

  • Data: Normal Distribution and Probability

    10/25/2011 A. MULTIPLE CHOICE QUESTIONS (50%) 1. Temperature is an example of a variable that uses a. the ratio scale b. the interval scale c. the ordinal scale d. either the ratio or the ordinal scale 2. The nominal scale of measurement has the properties of the a. ordinal scale b. only interval scale c. ratio scale d. None of these alternatives is correct. 3. Statistical studies in which researchers control variables of interest are a. experimental studies b. control observational...

    Arithmetic mean, Normal distribution, Probability density function 1344  Words | 9  Pages

  • Homework: Random Variable and Probability Distribution

    Math 107 002 Homework 5 (due 13 Oct 2011) Fall 2011 Please use your calculators and give your final answers to 3 significant figures. Show your work for full credit. Please state clearly all assumptions made. 1. Classify each random variable as discrete or continuous. (a) The number of visitors to the Museum of Science in Boston on a randomly selected day. (b) The camber-angle adjustment necessary for a front-end alignment. (c) The total number of pixels in a photograph produced by a digital camera...

    Continuous probability distribution, Discrete probability distribution, Probability density function 613  Words | 2  Pages

  • Binomial Distribution and Conway Maxwell Poisson

    A useful distribution for fitting discrete data: revival of the Conway–Maxwell–Poisson distribution Galit Shmueli, University of Maryland, College Park, USA Thomas P. Minka and Joseph B. Kadane, Carnegie Mellon University, Pittsburgh, USA Sharad Borle Rice University, Houston, USA and Peter Boatwright Carnegie Mellon University, Pittsburgh, USA [Received June 2003. Revised December 2003] Summary. A useful discrete distribution (the Conway–Maxwell–Poisson distribution) is revived ...

    Bernoulli distribution, Binomial distribution, Discrete distributions 5836  Words | 59  Pages

  • Normal Distribution

    deviation =10.59 3. If the variance is 846, what is the standard deviation? Solution: standard deviation = square root of variance = sqrt(846) = 29.086 4. If we have the following data 34, 38, 22, 21, 29, 37, 40, 41, 22, 20, 49, 47, 20, 31, 34, 66 Draw a stem and leaf. Discuss the shape of the distribution. Solution: 2 3 4 5 6 | | | | | 219200 48714 0197 6 This distribution is right skewed (positively skewed) because the “tail” extends to the right. 5. What type of relationship is shown by this...

    Arithmetic mean, Mean, Median 2715  Words | 7  Pages

  • Computational Aspects of Normal Distribution

    not to explain any more the usefulness of normal distribution in decision-making process no matter whether in social sciences or in natural sciences. Nor is the purpose of making any discussions on the theory of how it can be derived. The only objective of writing this article is to acquaint the enthusiastic readers (specially students) with the simple procedure ( iterative procedure) for finding the numerical value of a normally distributed variable. The procedure is simple in the sense that the students...

    Computer, Decimal, Normal distribution 1723  Words | 6  Pages

  • Normal Distribution

    C H A P T E R 6 The Normal Distribution Objectives Outline After completing this chapter, you should be able to 1 2 3 Identify distributions as symmetric or skewed. 4 Find probabilities for a normally distributed variable by transforming it into a standard normal variable. Introduction 6–1 Normal Distributions Identify the properties of a normal distribution. Find the area under the standard normal distribution, given various z values. 5 Find...

    Binomial distribution, Cumulative distribution function, Normal distribution 16101  Words | 129  Pages

  • NORMAL DISTRIBUTION AND SAMPLING

    HOMEWORK 2 FROM CHAPTER 6 and 7, NORMAL DISTRIBUTION AND SAMPLING Instructor: Asiye Aydilek PART 1- Multiple Choice Questions ____ 1. For the standard normal probability distribution, the area to the left of the mean is a. –0.5 c. any value between 0 to 1 b. 0.5 d. 1 Answer: B The total area under the curve is 1. The area on the left is the half of 1 which is 0.5. ____ 2. Which of the following is not a characteristic of the normal probability distribution? a. The mean and median are equal ...

    Continuous probability distribution, Cumulative distribution function, Normal distribution 477  Words | 4  Pages

  • Normal Distribution and Engineering Statistics Semester

    April 2013. SPECIAL DISTRIBUTIONS I. Concept of probability (3%) 1. Explain why the distribution B(n,p) can be approximated by Poisson distribution with parameter if n tends to infinity, p 0, and = np can be considered constant. 2. Show that – and + are the turning points in the graph of the p.d.f. of normal distribution with mean and standard deviation . 3. What is the relationship between exponential distribution and Poisson distribution? II. Computation...

    Cumulative distribution function, Exponential distribution, Normal distribution 423  Words | 2  Pages

  • The Poisson Probability Distribution

    The Poisson probability distribution, named after the French mathematician Siméon-Denis. Poisson is another important probability distribution of a discrete random variable that has a large number of applications. Suppose a washing machine in a Laundromat breaks down an average of three times a month. We may want to find the probability of exactly two breakdowns during the next month. This is an example of a Poisson probability distribution problem. Each breakdown is called an occurrence in Poisson...

    Continuous probability distribution, Discrete probability distribution, Poisson distribution 529  Words | 2  Pages

  • Road Rage

    A coin is tossed four times. The probability is ¼ or 0.25 that all four tosses will result in a head face up. Answer Correct Answer: False A firm offers routine physical examinations as part of a health service program for its employees. The exams showed that 8% of the employees needed corrective shoes, 15% needed major dental work and 3% needed both corrective shoes and major dental work. What is the probability that an employee selected at random will need either corrective shoes...

    Binomial distribution, Cumulative distribution function, Discrete probability distribution 870  Words | 4  Pages

  • Applied Probability and Statistics

    APPLIED PROBABILITY AND STATISTICS APPLIED PROBABILITY AND STATISTICS DEPARTMENT OF COMPUTER SCIENCE DEPARTMENT OF COMPUTER SCIENCE STATISTICAL DISTRIBUTION STATISTICAL DISTRIBUTION SUBMITTED BY – PREETISH MISHRA (11BCE0386) NUPUR KHANNA (11BCE0254) SUBMITTED BY – PREETISH MISHRA (11BCE0386) NUPUR KHANNA (11BCE0254) SUBMITTED TO – PROFESSOR SUJATHA V. SUBMITTED TO – PROFESSOR SUJATHA V...

    Continuous probability distribution, Cumulative distribution function, Normal distribution 4331  Words | 22  Pages

  • Datastor Case Study - Stats Probabilitiy and Binomials

    their side. Case Study Questions 1. If the DataStor DS1000 hard drive production process at DataStor Company is “in control”, what percentage of the drives produced would be considered to be in nonconformance by Four-D? In other words, what is the likelihood (probability) that the PDQ test score of a drive tested at DataStor will fall below 6.2? The probability that a PDQ test score of a drive tested at DataStor will fall below 6.2 is .38%. We arrived at this conclusion based on DataStor’s...

    Arithmetic mean, Binomial distribution, Cumulative distribution function 1375  Words | 7  Pages

  • Continuous Random Variable

    random variable because the time is being measured. All possible results for the variable time (t) would be greater than &gt; 0. b) The weight of a T-bone steak is a continuous random variable because the weight of the steak is measured. All the possible results for the weight of the T-bone steak would be positive numbers making the variable weight (w) &gt; greater than 0. c) The number of free throw attempts before the first shot is made is a discrete random variable because...

    Continuous probability distribution, Discrete probability distribution, Probability density function 694  Words | 4  Pages

  • Probability Cheatsheet 140718

    Probability Cheatsheet Expected Value, Linearity, and Symmetry Simpson’s Paradox c c c c P (A | B, C) < P (A | B , C) and P (A | B, C ) < P (A | B , C ) Compiled by William Chen (@wzchen) with contributions from Sebastian Chiu and Yuan Jiang. Material based off of Joe Blitzstein’s (@stat110) Intro to Probability lectures (http://stat110.net) and Blitzstein/Hwang’s Intro to Probability textbook (link). Share comments at http://github.com/wzchen/probability_cheatsheet. Counting c yet still...

    Cumulative distribution function, Expected value, Normal distribution 8564  Words | 7  Pages

  • Normal Distribution and Exhibit

    coefficient of variation equals a. 0.1125% b. 11.25% c. 203.12% d. 0.20312% ____3. In a binomial experiment, which one(s) of the following is (are) true? (i) The probability of success in the second trial is dependent on the outcome in the first trial. (ii) Only two outcomes are possible in each trial. (iii) The probability of success in each trial is always equal to the probability of failure. (iv) The expected value is always greater than or equal to the variance. a. (ii)...

    Cauchy distribution, Cumulative distribution function, Moment 469  Words | 3  Pages

  • Probability Theory

    be able to ONEDefine probability. TWO Describe the classical, empirical, and subjective approaches to probability. THREEUnderstand the terms experiment, event, outcome, permutation, and combination. FOURDefine the terms conditional probability and joint probability. FIVE Calculate probabilities applying the rules of addition and multiplication. SIXUse a tree diagram to organize and compute probabilities. SEVEN Calculate a probability using Bayes theorem. What is probability There is really no answer...

    Bayes' theorem, Bayesian probability, Conditional probability 2902  Words | 4  Pages

  • Random Variable and Density Function

    number of cars that pass through. Suppose the probabilities are 1/12, 1/12, 1/4, 1/4, 1/6, and 1/6, respectively, that the attendant receives $7, $9, $11, $13, $15, or $17 between 4:00 P. M. and 5:00 P. M. on any sunny Friday. Find the attendant’s expected earnings for this particular period. 4.7 By investing in a particular stock, a person can make a profit in one year of $4000 with probability 0.3 or take a loss of $1000 with probability 0.7. What is this person’s expected gain? 4.10 Two tire-quality...

    Cumulative distribution function, Expected value, Moment 868  Words | 3  Pages

  • Probability Distribution Case

    Chapter 6 Continuous Probability Distributions Case Problem: Specialty Toys 1. Information provided by the forecaster At x = 30,000, [pic] [pic] Normal distribution [pic] [pic] 2. @ 15,000 [pic] P(stockout) = 1 - .1635 = .8365 @ 18,000 [pic] P(stockout) = 1 - .3483 = .6517 @ 24,000 [pic] P(stockout) = 1 - .7823 = .2177 @ 28,000 [pic] ...

    Continuous probability distribution, Normal distribution, Operations research 590  Words | 5  Pages

  • Math221 Discussion Questions

    Example “initial” DEVRY MATH221 Discussion posts This is a collection DEVRY Math221 “Statistics for Decision Making” Discussion posts. This class is set up as a 8-week class where in the first 7-weeks you must post 3 discussion posts. These posts should be viewed as the ‘initial’ posts for each week. Normally the 2nd and 3rd posts each week are responses to other students. These discussions make up ~14% of the class so they are very important, and an easy way to get maximum points! These...

    Binomial distribution, Confidence interval, Normal distribution 563  Words | 3  Pages

  • Chi-square Distribution

    2.3. The Chi-Square Distribution One of the most important special cases of the gamma distribution is the chi-square distribution because the sum of the squares of independent normal random variables with mean zero and standard deviation one has a chi-square distribution. This section collects some basic properties of chi-square random variables, all of which are well known; see Hogg and Tanis [6]. A random variable X has a chi-square distribution with n degrees of freedom if it is a gamma...

    Chi-square distribution, Cumulative distribution function, Exponential distribution 882  Words | 3  Pages

  • Stats Paper

    1. A sample of 20 employee’s salaries from a large company results in the following salaries (in thousands of dollars) for this year. 28 31 34 35 37 47 42 42 49 41 42 60 52 52 51 72 67 61 75 77. What is the interquartile range (in thousands) of this data set? (A) 21.5 (B) 10 (C) 50 (D) 23 (E) correct answer is not given 2. Please refer to the previous question. Suppose each employee in the company receives $3,000 raise for next year. The interquartile range (IQR) of the salaries will: (A)...

    Arithmetic mean, Mean, Median 1882  Words | 7  Pages

  • Fundamentals of Probability and Statistics for Engineers

    TLFeBOOK FUNDAMENTALS OF PROBABILITY AND STATISTICS FOR ENGINEERS T.T. Soong State University of New York at Buffalo, Buffalo, New York, USA TLFeBOOK TLFeBOOK FUNDAMENTALS OF PROBABILITY AND STATISTICS FOR ENGINEERS TLFeBOOK USA TLFeBOOK Copyright  2004 John Wiley & Sons Ltd, The Atrium, Southern G ate, Chichester, West...

    Continuous probability distribution, Cumulative distribution function, Discrete probability distribution 81505  Words | 319  Pages

  • Conditional Probability

    Basic Probability Notes Probability— the relative frequency or likelihood that a specific event will occur. If the event is A, then the probability that A will occur is denoted P(A). Example: Flip a coin. What is the probability of heads? This is denoted P(heads). Properties of Probability 1. The probability of an event E always lies in the range of 0 to 1; i.e., 0 ≤ P( E ) ≤ 1. Impossible event—an event that absolutely cannot occur; probability is zero. Example: Suppose you roll a normal die...

    Bayes' theorem, Bayesian probability, Conditional probability 1587  Words | 5  Pages

  • Chapter 1: Discrete and Continuous Probability Distributions

    TEM1116 Probability and Statistics Tri1 2013/14 Chapter 1 Chapter 1: Discrete and Continuous Probability Distributions Section 1: Probability Contents: 1.1 1.2 1.3 1.4 1.5 Some basics of probability theory Axioms, Interpretations, and Properties of Probability Counting Techniques and Probability Conditional Probability Independence TEM1116 1 TEM1116 Probability and Statistics Tri1 2013/14 Chapter 1 1.1 Basics of Probability Theory Probability refers to the study...

    Continuous probability distribution, Cumulative distribution function, Discrete probability distribution 5123  Words | 22  Pages

  • Why Education Is More Important Than Money

    Subject : Probability and Statistics = PS Strand 1: Introduction to Statistics. Strand 2: Organizing Data. Strand 3 : Averages and Variation Strand 4: Elementary Probability Theory. Strand 5: The Binomial Probability Distribution and Related Topics. Strand 6: Normal Distributions. Strand 7: Introduction to Sample Distributions. Benchmark Code Subject (M, S, SS, LA).Grade#.Strand#.Standard#. Benchmark# Example: PS.1.4.3 – Probability and Statistics, Strand 1, Standard 4, Benchmark 3 Strand: 1 INTRODUCTION...

    Binomial distribution, Cumulative distribution function, Normal distribution 2045  Words | 6  Pages

  • Probability Theory

    I. Probability Theory * A branch of mathematics concerned with the analysis of random phenomena. The outcome of a random event cannot be determined before it occurs, but it may be any one of several possible outcomes. The actual outcome is considered to be determined by chance. * The word probability has several meanings in ordinary conversation. Two of these are particularly important for the development and applications of the mathematical theory of probability. One is the interpretation...

    Event, Null hypothesis, Probability 1874  Words | 7  Pages

  • Probability

    Probability 1.) AE-2 List the enduring understandings for a content-area unit to be implemented over a three- to five- week time period. Explain how the enduring understandings serve to contextualize (add context or way of thinking to) the content-area standards. Unit: Data and Probability Time: 3 weeks max Enduring Understanding: “Student Will Be Able To: - Know what probability is (chance, fairness, a way to observe our random world, the different representations)
 - Know what the...

    Event, Normal distribution, Probability 496  Words | 2  Pages

  • Quiz for 5wk Statistics

    1. State whether the variable is discrete or continuous. The # of keys on each student's key chain. 2. Decide whether the experiment is a binomial experiment. Explain why by citing the properties of binomial experiments. Testing a pain reliever using 20 people to determine if it is effective. The random variable represents the number of people who find the pain reliever to be effective. 3. Use the binomial probability distribution to answer the following probability questions. According to...

    Binomial distribution, Cumulative distribution function, Discrete probability distribution 942  Words | 4  Pages

  • Statistique Random Variable

    SIDS31081 - Statistics Refresher 2006 – 2007 Exercises (Probability and Random Variables) Exercise 1 Suppose that we have a sample space with five equally likely experimental outcomes : E1,E2,E3,E4,E5. Let A = {E1,E2} B = {E3,E4} C = {E2,E3,E5} a. Find P(A), P(B), P(C). b. Find P(A U B) . Are A and B mutually exclusive? c. Find Ac, Bc, P(Ac), P(Bc). d. Find A U Bc and P(A U Bc) e. Find P(B U C) Exercise 2 A committee with two members is to be selected from a collection of 30...

    ABO blood group system, Blood, Blood type 608  Words | 4  Pages

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