4.5 Comparing Discrete Probability Distributions.

Slides:

Advertisements

Similar presentations

Probability Distribution

Advertisements

Chapter 4: Section 6 Compound Probability.

HYPERGEOMETRIC DISTRIBUTION Dependent Trials. Learning Goals I can use terminology such as probability distribution, random variable, relative frequency.

If X has the binomial distribution with n trials and probability p of success on each trial, then possible values of X are 0, 1, 2…n. If k is any one of.

Special random variables Chapter 5 Some discrete or continuous probability distributions.

Discrete Uniform Distribution

ฟังก์ชั่นการแจกแจงความน่าจะเป็น แบบไม่ต่อเนื่อง Discrete Probability Distributions.

Statistics for Managers Using Microsoft Excel, 4e © 2004 Prentice-Hall, Inc. Chap 5-1 Chapter 5 Some Important Discrete Probability Distributions Statistics.

Probability Distribution

Discrete Probability Distributions Introduction to Business Statistics, 5e Kvanli/Guynes/Pavur (c)2000 South-Western College Publishing.

Random Variables November 23, Discrete Random Variables A random variable is a variable whose value is a numerical outcome of a random phenomenon.

Engineering Probability and Statistics - SE-205 -Chap 3 By S. O. Duffuaa.

Class notes for ISE 201 San Jose State University

The Binomial Distribution. Introduction # correct TallyFrequencyP(experiment)P(theory) Mix the cards, select one & guess the type. Repeat 3 times.

Discrete and Continuous Distributions G. V. Narayanan.

Discrete Probability Distributions Binomial Distribution Poisson Distribution Hypergeometric Distribution.

Kate Schwartz & Lexy Ellingwood CHAPTER 8 REVIEW: THE BINOMIAL AND GEOMETRIC DISTRIBUTIONS.

7.3 Probabilities when Outcomes are Equally Likely.

Lesson 6 – 2b Hyper-Geometric Probability Distribution.

Unit 6 – Data Analysis and Probability

Binomial & Geometric Random Variables §6-3. Goals: Binomial settings and binomial random variables Binomial probabilities Mean and standard deviation.

McGraw-Hill/Irwin Copyright © 2007 by The McGraw-Hill Companies, Inc. All rights reserved. Discrete Random Variables Chapter 4.

Section 15.8 The Binomial Distribution. A binomial distribution is a discrete distribution defined by two parameters: The number of trials, n The probability.

Notes – Chapter 17 Binomial & Geometric Distributions.

Binomial Distributions

The Binomial and Geometric Distribution

Chapter 7 Lesson 7.5 Random Variables and Probability Distributions

You are familiar with the term “average”, as in arithmetical average of a set of numbers (test scores for example) – we used the symbol to stand for this.

Discrete Probability Distributions. Random Variable Random variable is a variable whose value is subject to variations due to chance. A random variable.

Binomial Probability Distribution

Math 22 Introductory Statistics Chapter 8 - The Binomial Probability Distribution.

Copyright © 2010 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Chapter 5 Discrete Random Variables.

McGraw-Hill/IrwinCopyright © 2009 by The McGraw-Hill Companies, Inc. All Rights Reserved. Chapter 5 Discrete Random Variables.

Copyright © 2010, 2007, 2004 Pearson Education, Inc. All Rights Reserved. Statistics Section 5-6 Normal as Approximation to Binomial.

Probability Distributions u Discrete Probability Distribution –Discrete vs. continuous random variables »discrete - only a countable number of values »continuous.

Math b (Discrete) Random Variables, Binomial Distribution.

Chapter 5 Discrete Probability Distributions. Random Variable A numerical description of the result of an experiment.

8.1 Continuous Probability Distribution. Discrete Vs. Continuous Last chapter we dealt mostly with discrete data (number of things happening that usually.

Methodology Solving problems with known distributions 1.

The Binomial Distribution

4.2 Binomial Distributions

Statistics 3502/6304 Prof. Eric A. Suess Chapter 4.

Ch. 15H continued. * -applied to experiments with replacement ONLY(therefore…..independent events only) * -Note: For DEPENDENT events we use the “hypergeometric.

7.1 Continuous Probability Distribution. Discrete Vs. Continuous Last chapter we dealt mostly with discrete data (number of things happening that usually.

6.2 BINOMIAL PROBABILITIES.  Features  Fixed number of trials (n)  Trials are independent and repeated under identical conditions  Each trial has.

This is a discrete distribution. Situations that can be modeled with the binomial distribution must have these 4 properties: Only two possible outcomes.

Notes – Chapter 17 Binomial & Geometric Distributions.

Discrete Probability Distributions Chapter 4. § 4.2 Binomial Distributions.

1 7.3 RANDOM VARIABLES When the variables in question are quantitative, they are known as random variables. A random variable, X, is a quantitative variable.

Special Discrete Distributions: Geometric Distributions.

4.4 Hypergeometric Distribution

Chapter 3 Discrete Random Variables and Probability Distributions  Random Variables.2 - Probability Distributions for Discrete Random Variables.3.

6.2 Binomial Distributions Recognize and calculate probabilities that are binomial distributions Use the probabilities and expected values to make decision.

Copyright © 2011 by The McGraw-Hill Companies, Inc. All rights reserved. McGraw-Hill/Irwin Chapter 5 Discrete Random Variables.

Chap 5-1 Chapter 5 Discrete Random Variables and Probability Distributions Statistics for Business and Economics 6 th Edition.

Discrete Probability Distributions Chapter 4. § 4.3 More Discrete Probability Distributions.

Unit 3: Probability.  You will need to be able to describe how you will perform a simulation  Create a correspondence between random numbers and outcomes.

Ch3.5 Hypergeometric Distribution

Math 4030 – 4a More Discrete Distributions

Discrete Random Variables

Discrete Random Variables

Discrete Probability Distributions

3.4 The Binomial Distribution

The Binomial and Geometric Distributions

Bernoulli Trials Two Possible Outcomes Trials are independent.

Binomial Distributions

6.1 Probability Distribution

The Binomial Distributions

Each Distribution for Random Variables Has:

Presentation transcript:

4.5 Comparing Discrete Probability Distributions

So far Uniform Binomial Hypergeometric

When to use what? Random Variable Independent or Dependent? Pass/Fail, true/false or other?

Compare the following A card is picked from a deck and then replaced. This happens 5 times. Find probability distribution for the number of face cards. 5 cards are dealt from a deck of cards. Find the probability distribution for the number of face cards.

UniformBinomialHypergeometric Parameters and what they mean N=number of trialsn= number of Trials p= Prob of success on individual trial q= Prob of failure on individual trial n= size of population r= number of trials a= number of successful items available Definition or Random Variable X Value of the outcome Number of successful outcomes Probability Formula Expectation Formula CharacteristicsAll items are equally likely A single Trial Trials are independent Successes are counted Trials are Dependent Successes are counted

Assignment Pg 185 #’s 1-7 Review Page 188 #’s 1-14 Practice Test pg 191 #’s 1-16