Week Four Discussion 2 1. In your own words‚ describe two main differences between classical and empirical probabilities. The differences between classical and empirical probabilities are that classical assumes that all outcomes are likely to occur‚ while empirical involves actually physically observing and collecting the information. 2. Gather coins you find around your home or in your pocket or purse. You will need an even number of coins (any denomination) between 16 and 30. You do not
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14. If x has the probability distribution f(x) = 12x for x = 1‚2‚3‚…‚ show that E(2X) does not exist. This is famous Petersburg paradox‚ according to which a player’s expectation is infinite (does not exist) if he is to receive 2x dollars when‚ in a series of flips of a balanced coin‚ the first head appears on the xth flip. 17. The manager of a bakery knows that the number of chocolate cakes he can sell on any given day is a random variable having the probability distribution f(x) = 16 for x =
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1 Why probability and statistics? Is everything on this planet determined by randomness? This question is open to philosophical debate. What is certain is that every day thousands and thousands of engineers‚ scientists‚ business persons‚ manufacturers‚ and others are using tools from probability and statistics. The theory and practice of probability and statistics were developed during the last century and are still actively being refined and extended. In this book we will introduce the basic notions
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Chapter 5 Measures of Central Tendency: Introduction A measure of central tendency is a single value that attempts to describe a set of data by identifying the central position within that set of data. As such‚ measures of central tendency are sometimes called measures of central location. They are also classed as summary statistics. The mean (often called the average) is most likely the measure of central tendency that you are most familiar with‚ but there are others‚ such as the median and the
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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]
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DUNDALK INSTITUTE OF TECHNOLOGY | | | | | Bachelor of Science in Computing in Applications & Support - Semester 3 | Bachelor of Science in Computing in Networking & Support - Semester 3 | Bachelor of Science in Computing in Software Development - Semester 3 | | | Data Analysis for Computing | | Christmas 2010 | | | | | | | | | | | Dr. Fiona Lawless | | | | | | | Answer any FOUR questions | All questions carry
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Math in My Life This year in Algebra 2 class I have learn some very interesting and important topics. Throughout this past school year I have grown and learned how to use these newly learned skills and my understanding of algebra is now complete. In math class this year‚ I believe I did fairly well and received almost got all A’s. I think I passed this class is because math in general comes easy to me. I only studied in the beginning of the year‚ as the latter part of the year came much easier.
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MGT 601: Statistical Inference Lecture 03 Dr. MUMTAZ AHMED Objectives of Current Lecture In the current lecture: Introduction to Probability Definition and Basic concepts of probability Some basic questions related to probability Laws of probability Conditional probability Independent and Dependent Events Related Examples 2 Probability Probability (or likelihood) is a measure or estimation of how likely it is that something will happen or that a statement is true. For example
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Think Stats: Probability and Statistics for Programmers Version 1.6.0 Think Stats Probability and Statistics for Programmers Version 1.6.0 Allen B. Downey Green Tea Press Needham‚ Massachusetts Copyright © 2011 Allen B. Downey. Green Tea Press 9 Washburn Ave Needham MA 02492 Permission is granted to copy‚ distribute‚ and/or modify this document under the terms of the Creative Commons Attribution-NonCommercial 3.0 Unported License‚ which is available at http://creativecommons
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IPPR #: EDUC 530 Lesson Plan: Place Value‚ Integer‚ Computation |Teacher Candidate: |Course: EDUC 530 | |LESSON PREPARATION [before the lesson] | |Topic: Place Value‚ Integer‚ Computation |Concept: Regrouping
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