'Bernoulli trials' presentation slideshows

Applied Hydrology Hydrological Frequency Analysis

Applied Hydrology Hydrological Frequency Analysis. Prof. Ke-Sheng Cheng Department of Bioenvironmental Systems Engineering National Taiwan University. Outline. Introductory thoughts General interpretation of hydrological frequency analysis The general equation of frequency analysis

2.79k views • 204 slides

Lecture 2

Probability and Statistics Part 2: Statistics. Lecture 2. What is the probability of the weight at birth of any baby born being in 2440 g class?. Frequency distribution. p=0.0677. Birthweight < 3000 g How many of them?. Frequency distribution. 28.57%. Frequency distribution.

940 views • 71 slides

4: Probability

4: Probability. Part A: Concepts & binomial distributions Part B: Normal distributions. Definitions. Random variable ? a numerical quantity that takes on different values depending on chance Population ? the set of all possible values for a random variable

573 views • 48 slides

Random variables, distributions and limit theorems

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Chapter 3. Discrete Probability Distributions

Chapter 3. Discrete Probability Distributions. 3.1 The Binomial Distribution 3.2 The Geometric and Negative Binomial Distributions 3.3 The Hypergeometric Distribution 3.4 The Poisson Distribution 3.5 The Multinomial Distribution.

668 views • 44 slides

Chapter 8

Chapter 8. Sampling Distribution of a Statistic. Binomial Distribution. A binomial random variable X is the total number of successes in n independent Bernoulli trials, on which each trial, the probability of success is p. We say X is B ( n,p ).

479 views • 39 slides

Probability Distributions for Discrete Variables

Probability Distributions for Discrete Variables. Farrokh Alemi Ph.D. Professor of Health Administration and Policy College of Health and Human Services, George Mason University 4400 University Drive, Fairfax, Virginia 22030 703 993 1929 falemi@gmu.edu. Lecture Outline. What is probability?

444 views • 37 slides

Discrete Random Variables and Probability Distributions

1.19k views • 36 slides

Random Variable

Random Variable. A random variable X is a function that assign a real number, X ( ? ), to each outcome ? in the sample space of a random experiment. Domain of the random variable -- S Range of the random variable -- S x

1.3k views • 32 slides

Lecture 5

Lecture 5. The Micro-foundations of the Demand for Money - Part 2. State the general conditions for an interior solution for a risk averse utility maximising agent Show that the quadratic utility function does not meet all these conditions

547 views • 30 slides

22C:19 Discrete Math Discrete Probability

22C:19 Discrete Math Discrete Probability. Fall 2011 Sukumar Ghosh. Sample Space. DEFINITION . The sample space S of an experiment is the set of possible outcomes. An event E is a subset of the sample space. What is probability?. Probability distribution.

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797 views • 29 slides

690 views • 27 slides

Random Variables

Random Variables. Discrete: Bernoulli, Binomial, Geometric, Poisson Continuous: Uniform, Exponential, Gamma, Normal Expectation & Variance, Joint Distributions, Moment Generating Functions, Limit Theorems. Definition of random variable.

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Chapter 6: Binomial Probability Distributions

Chapter 6: Binomial Probability Distributions. In Chapter 6:. 6.1 Binomial Random Variables 6.2 Calculating Binomial Probabilities 6.3 Cumulative Probabilities 6.4 Probability Calculators 6.5 Expected Value and Variance .. 6.6 Using the Binomial Distribution to Help Make Judgments.

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CMSC 203 / 0201 Fall 2002

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Poisson Processes

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Flipping an unfair coin three times

Flipping an unfair coin three times. Consider the unfair coin with P(H) = 1/3 and P(T) = 2/3. If we flip this coin three times, the sample space S is the following set of ordered triples: S = {HHH, HHT, HTH, THH, TTH, THT, HTT, TTT}.

438 views • 16 slides

Probability & Statistics for Engineers & Scientists, by Walpole, Myers, Myers & Ye ~ Chapter 5 Notes

Probability & Statistics for Engineers & Scientists, by Walpole, Myers, Myers & Ye ~ Chapter 5 Notes. Class notes for ISE 201 San Jose State University Industrial & Systems Engineering Dept. Steve Kennedy. Discrete Probability Distributions.

2.15k views • 15 slides